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TVM cleanup #2777

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TVM cleanup

TVM cleanup #2777

GitHub Actions / TT-Forge-FE Tests failed Feb 26, 2025 in 0s

672 tests run, 68 passed, 136 skipped, 468 failed.

Annotations

Check failure on line 117 in forge/test/mlir/operators/eltwise_binary/test_eltwise_binary.py

See this annotation in the file changed.

@github-actions github-actions / TT-Forge-FE Tests

test_eltwise_binary.test_less[shape_x1-shape_y1] 

File "/opt/ttforge-toolchain/venv/lib/python3.10/site-packages/forge/tvm_calls/relay/op/forge.py", line 19
    from tvm.relay.dataflow_pattern import *from .reportify import dump_graph
                                            ^^^^
SyntaxError: invalid syntax
Raw output 
shape_x = (1, 64, 28, 28), shape_y = (1, 64, 28, 28)

    @pytest.mark.parametrize(
        "shape_x, shape_y",
        [
            ((1, 128, 28, 28), (1, 128, 28, 28)),
            ((1, 64, 28, 28), (1, 64, 28, 28)),
            ((1, 256, 28, 28), (1, 256, 28, 28)),
            ((1, 128, 14, 14), (1, 128, 14, 14)),
            ((1, 128, 56, 56), (1, 128, 56, 56)),
            ((1, 32, 64, 64), (1, 32, 64, 64)),
            ((1, 512, 7, 7), (1, 512, 7, 7)),
            ((1, 32, 32, 32), (1, 32, 32, 32)),
        ],
    )
    @pytest.mark.push
    def test_less(shape_x, shape_y):
        class Less(nn.Module):
            def __init__(self):
                super().__init__()
    
            def forward(self, x, y):
                return torch.less(x, y)
    
        x = torch.rand(shape_x)
        y = torch.rand(shape_y)
    
        inputs = [x, y]
    
        framework_model = Less()
>       compiled_model = forge.compile(framework_model, sample_inputs=inputs)

forge/test/mlir/operators/eltwise_binary/test_eltwise_binary.py:117: 
_ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ 
/opt/ttforge-toolchain/venv/lib/python3.10/site-packages/forge/compile.py:251: in compile_main
    return forge_compile_from_context(compile_context)
/opt/ttforge-toolchain/venv/lib/python3.10/site-packages/forge/compile.py:293: in forge_compile_from_context
    next_stage = stage_to_func[current_stage](context)
/opt/ttforge-toolchain/venv/lib/python3.10/site-packages/forge/compile.py:671: in generate_initial_graph
    module, module_inputs = convert_to_forge_module(
/opt/ttforge-toolchain/venv/lib/python3.10/site-packages/forge/compile.py:1032: in convert_to_forge_module
    forge_module, dev_types, module_inputs = generate_forge_module(
/opt/ttforge-toolchain/venv/lib/python3.10/site-packages/forge/tvm_to_python.py:2062: in generate_forge_module
    module_writers, flattened_inputs = compile_tvm_to_python(
/opt/ttforge-toolchain/venv/lib/python3.10/site-packages/forge/tvm_to_python.py:2149: in compile_tvm_to_python
    from forge.tvm_calls.forge_compile import load_tvm_graph
/opt/ttforge-toolchain/venv/lib/python3.10/site-packages/forge/tvm_calls/forge_compile.py:36: in <module>
    from forge.tvm_calls.relay.op.forge import verify_tvm_compile, flatten_IO, compile_for_forge, partition_for_forge
_ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ 

    # SPDX-FileCopyrightText:  2024 Tenstorrent AI ULC
    #
    # SPDX-License-Identifier: Apache-2.0
>   from .forge import *
E     File "/opt/ttforge-toolchain/venv/lib/python3.10/site-packages/forge/tvm_calls/relay/op/forge.py", line 19
E       from tvm.relay.dataflow_pattern import *from .reportify import dump_graph
E                                               ^^^^
E   SyntaxError: invalid syntax

/opt/ttforge-toolchain/venv/lib/python3.10/site-packages/forge/tvm_calls/relay/op/__init__.py:4: SyntaxError

Check failure on line 117 in forge/test/mlir/operators/eltwise_binary/test_eltwise_binary.py

See this annotation in the file changed.

@github-actions github-actions / TT-Forge-FE Tests

test_eltwise_binary.test_less[shape_x3-shape_y3] 

File "/opt/ttforge-toolchain/venv/lib/python3.10/site-packages/forge/tvm_calls/relay/op/forge.py", line 19
    from tvm.relay.dataflow_pattern import *from .reportify import dump_graph
                                            ^^^^
SyntaxError: invalid syntax
Raw output 
shape_x = (1, 128, 14, 14), shape_y = (1, 128, 14, 14)

    @pytest.mark.parametrize(
        "shape_x, shape_y",
        [
            ((1, 128, 28, 28), (1, 128, 28, 28)),
            ((1, 64, 28, 28), (1, 64, 28, 28)),
            ((1, 256, 28, 28), (1, 256, 28, 28)),
            ((1, 128, 14, 14), (1, 128, 14, 14)),
            ((1, 128, 56, 56), (1, 128, 56, 56)),
            ((1, 32, 64, 64), (1, 32, 64, 64)),
            ((1, 512, 7, 7), (1, 512, 7, 7)),
            ((1, 32, 32, 32), (1, 32, 32, 32)),
        ],
    )
    @pytest.mark.push
    def test_less(shape_x, shape_y):
        class Less(nn.Module):
            def __init__(self):
                super().__init__()
    
            def forward(self, x, y):
                return torch.less(x, y)
    
        x = torch.rand(shape_x)
        y = torch.rand(shape_y)
    
        inputs = [x, y]
    
        framework_model = Less()
>       compiled_model = forge.compile(framework_model, sample_inputs=inputs)

forge/test/mlir/operators/eltwise_binary/test_eltwise_binary.py:117: 
_ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ 
/opt/ttforge-toolchain/venv/lib/python3.10/site-packages/forge/compile.py:251: in compile_main
    return forge_compile_from_context(compile_context)
/opt/ttforge-toolchain/venv/lib/python3.10/site-packages/forge/compile.py:293: in forge_compile_from_context
    next_stage = stage_to_func[current_stage](context)
/opt/ttforge-toolchain/venv/lib/python3.10/site-packages/forge/compile.py:671: in generate_initial_graph
    module, module_inputs = convert_to_forge_module(
/opt/ttforge-toolchain/venv/lib/python3.10/site-packages/forge/compile.py:1032: in convert_to_forge_module
    forge_module, dev_types, module_inputs = generate_forge_module(
/opt/ttforge-toolchain/venv/lib/python3.10/site-packages/forge/tvm_to_python.py:2062: in generate_forge_module
    module_writers, flattened_inputs = compile_tvm_to_python(
/opt/ttforge-toolchain/venv/lib/python3.10/site-packages/forge/tvm_to_python.py:2149: in compile_tvm_to_python
    from forge.tvm_calls.forge_compile import load_tvm_graph
/opt/ttforge-toolchain/venv/lib/python3.10/site-packages/forge/tvm_calls/forge_compile.py:36: in <module>
    from forge.tvm_calls.relay.op.forge import verify_tvm_compile, flatten_IO, compile_for_forge, partition_for_forge
_ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ 

    # SPDX-FileCopyrightText:  2024 Tenstorrent AI ULC
    #
    # SPDX-License-Identifier: Apache-2.0
>   from .forge import *
E     File "/opt/ttforge-toolchain/venv/lib/python3.10/site-packages/forge/tvm_calls/relay/op/forge.py", line 19
E       from tvm.relay.dataflow_pattern import *from .reportify import dump_graph
E                                               ^^^^
E   SyntaxError: invalid syntax

/opt/ttforge-toolchain/venv/lib/python3.10/site-packages/forge/tvm_calls/relay/op/__init__.py:4: SyntaxError

Check failure on line 117 in forge/test/mlir/operators/eltwise_binary/test_eltwise_binary.py

See this annotation in the file changed.

@github-actions github-actions / TT-Forge-FE Tests

test_eltwise_binary.test_less[shape_x5-shape_y5] 

File "/opt/ttforge-toolchain/venv/lib/python3.10/site-packages/forge/tvm_calls/relay/op/forge.py", line 19
    from tvm.relay.dataflow_pattern import *from .reportify import dump_graph
                                            ^^^^
SyntaxError: invalid syntax
Raw output 
shape_x = (1, 32, 64, 64), shape_y = (1, 32, 64, 64)

    @pytest.mark.parametrize(
        "shape_x, shape_y",
        [
            ((1, 128, 28, 28), (1, 128, 28, 28)),
            ((1, 64, 28, 28), (1, 64, 28, 28)),
            ((1, 256, 28, 28), (1, 256, 28, 28)),
            ((1, 128, 14, 14), (1, 128, 14, 14)),
            ((1, 128, 56, 56), (1, 128, 56, 56)),
            ((1, 32, 64, 64), (1, 32, 64, 64)),
            ((1, 512, 7, 7), (1, 512, 7, 7)),
            ((1, 32, 32, 32), (1, 32, 32, 32)),
        ],
    )
    @pytest.mark.push
    def test_less(shape_x, shape_y):
        class Less(nn.Module):
            def __init__(self):
                super().__init__()
    
            def forward(self, x, y):
                return torch.less(x, y)
    
        x = torch.rand(shape_x)
        y = torch.rand(shape_y)
    
        inputs = [x, y]
    
        framework_model = Less()
>       compiled_model = forge.compile(framework_model, sample_inputs=inputs)

forge/test/mlir/operators/eltwise_binary/test_eltwise_binary.py:117: 
_ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ 
/opt/ttforge-toolchain/venv/lib/python3.10/site-packages/forge/compile.py:251: in compile_main
    return forge_compile_from_context(compile_context)
/opt/ttforge-toolchain/venv/lib/python3.10/site-packages/forge/compile.py:293: in forge_compile_from_context
    next_stage = stage_to_func[current_stage](context)
/opt/ttforge-toolchain/venv/lib/python3.10/site-packages/forge/compile.py:671: in generate_initial_graph
    module, module_inputs = convert_to_forge_module(
/opt/ttforge-toolchain/venv/lib/python3.10/site-packages/forge/compile.py:1032: in convert_to_forge_module
    forge_module, dev_types, module_inputs = generate_forge_module(
/opt/ttforge-toolchain/venv/lib/python3.10/site-packages/forge/tvm_to_python.py:2062: in generate_forge_module
    module_writers, flattened_inputs = compile_tvm_to_python(
/opt/ttforge-toolchain/venv/lib/python3.10/site-packages/forge/tvm_to_python.py:2149: in compile_tvm_to_python
    from forge.tvm_calls.forge_compile import load_tvm_graph
/opt/ttforge-toolchain/venv/lib/python3.10/site-packages/forge/tvm_calls/forge_compile.py:36: in <module>
    from forge.tvm_calls.relay.op.forge import verify_tvm_compile, flatten_IO, compile_for_forge, partition_for_forge
_ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ 

    # SPDX-FileCopyrightText:  2024 Tenstorrent AI ULC
    #
    # SPDX-License-Identifier: Apache-2.0
>   from .forge import *
E     File "/opt/ttforge-toolchain/venv/lib/python3.10/site-packages/forge/tvm_calls/relay/op/forge.py", line 19
E       from tvm.relay.dataflow_pattern import *from .reportify import dump_graph
E                                               ^^^^
E   SyntaxError: invalid syntax

/opt/ttforge-toolchain/venv/lib/python3.10/site-packages/forge/tvm_calls/relay/op/__init__.py:4: SyntaxError

Check failure on line 117 in forge/test/mlir/operators/eltwise_binary/test_eltwise_binary.py

See this annotation in the file changed.

@github-actions github-actions / TT-Forge-FE Tests

test_eltwise_binary.test_less[shape_x7-shape_y7] 

File "/opt/ttforge-toolchain/venv/lib/python3.10/site-packages/forge/tvm_calls/relay/op/forge.py", line 19
    from tvm.relay.dataflow_pattern import *from .reportify import dump_graph
                                            ^^^^
SyntaxError: invalid syntax
Raw output 
shape_x = (1, 32, 32, 32), shape_y = (1, 32, 32, 32)

    @pytest.mark.parametrize(
        "shape_x, shape_y",
        [
            ((1, 128, 28, 28), (1, 128, 28, 28)),
            ((1, 64, 28, 28), (1, 64, 28, 28)),
            ((1, 256, 28, 28), (1, 256, 28, 28)),
            ((1, 128, 14, 14), (1, 128, 14, 14)),
            ((1, 128, 56, 56), (1, 128, 56, 56)),
            ((1, 32, 64, 64), (1, 32, 64, 64)),
            ((1, 512, 7, 7), (1, 512, 7, 7)),
            ((1, 32, 32, 32), (1, 32, 32, 32)),
        ],
    )
    @pytest.mark.push
    def test_less(shape_x, shape_y):
        class Less(nn.Module):
            def __init__(self):
                super().__init__()
    
            def forward(self, x, y):
                return torch.less(x, y)
    
        x = torch.rand(shape_x)
        y = torch.rand(shape_y)
    
        inputs = [x, y]
    
        framework_model = Less()
>       compiled_model = forge.compile(framework_model, sample_inputs=inputs)

forge/test/mlir/operators/eltwise_binary/test_eltwise_binary.py:117: 
_ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ 
/opt/ttforge-toolchain/venv/lib/python3.10/site-packages/forge/compile.py:251: in compile_main
    return forge_compile_from_context(compile_context)
/opt/ttforge-toolchain/venv/lib/python3.10/site-packages/forge/compile.py:293: in forge_compile_from_context
    next_stage = stage_to_func[current_stage](context)
/opt/ttforge-toolchain/venv/lib/python3.10/site-packages/forge/compile.py:671: in generate_initial_graph
    module, module_inputs = convert_to_forge_module(
/opt/ttforge-toolchain/venv/lib/python3.10/site-packages/forge/compile.py:1032: in convert_to_forge_module
    forge_module, dev_types, module_inputs = generate_forge_module(
/opt/ttforge-toolchain/venv/lib/python3.10/site-packages/forge/tvm_to_python.py:2062: in generate_forge_module
    module_writers, flattened_inputs = compile_tvm_to_python(
/opt/ttforge-toolchain/venv/lib/python3.10/site-packages/forge/tvm_to_python.py:2149: in compile_tvm_to_python
    from forge.tvm_calls.forge_compile import load_tvm_graph
/opt/ttforge-toolchain/venv/lib/python3.10/site-packages/forge/tvm_calls/forge_compile.py:36: in <module>
    from forge.tvm_calls.relay.op.forge import verify_tvm_compile, flatten_IO, compile_for_forge, partition_for_forge
_ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ 

    # SPDX-FileCopyrightText:  2024 Tenstorrent AI ULC
    #
    # SPDX-License-Identifier: Apache-2.0
>   from .forge import *
E     File "/opt/ttforge-toolchain/venv/lib/python3.10/site-packages/forge/tvm_calls/relay/op/forge.py", line 19
E       from tvm.relay.dataflow_pattern import *from .reportify import dump_graph
E                                               ^^^^
E   SyntaxError: invalid syntax

/opt/ttforge-toolchain/venv/lib/python3.10/site-packages/forge/tvm_calls/relay/op/__init__.py:4: SyntaxError

Check failure on line 150 in forge/test/mlir/operators/eltwise_binary/test_eltwise_binary.py

See this annotation in the file changed.

@github-actions github-actions / TT-Forge-FE Tests

test_eltwise_binary.test_greater[shape_x1-shape_y1] 

File "/opt/ttforge-toolchain/venv/lib/python3.10/site-packages/forge/tvm_calls/relay/op/forge.py", line 19
    from tvm.relay.dataflow_pattern import *from .reportify import dump_graph
                                            ^^^^
SyntaxError: invalid syntax
Raw output 
shape_x = (1, 64, 28, 28), shape_y = (1, 64, 28, 28)

    @pytest.mark.parametrize(
        "shape_x, shape_y",
        [
            ((1, 128, 28, 28), (1, 128, 28, 28)),
            ((1, 64, 28, 28), (1, 64, 28, 28)),
            ((1, 256, 28, 28), (1, 256, 28, 28)),
            ((1, 128, 14, 14), (1, 128, 14, 14)),
            ((1, 128, 56, 56), (1, 128, 56, 56)),
            ((1, 32, 64, 64), (1, 32, 64, 64)),
            ((1, 512, 7, 7), (1, 512, 7, 7)),
            ((1, 32, 32, 32), (1, 32, 32, 32)),
        ],
    )
    @pytest.mark.push
    def test_greater(shape_x, shape_y):
        class Greater(nn.Module):
            def __init__(self):
                super().__init__()
    
            def forward(self, x, y):
                return torch.greater(x, y)
    
        x = torch.rand(shape_x)
        y = torch.rand(shape_y)
    
        inputs = [x, y]
    
        framework_model = Greater()
>       compiled_model = forge.compile(framework_model, sample_inputs=inputs)

forge/test/mlir/operators/eltwise_binary/test_eltwise_binary.py:150: 
_ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ 
/opt/ttforge-toolchain/venv/lib/python3.10/site-packages/forge/compile.py:251: in compile_main
    return forge_compile_from_context(compile_context)
/opt/ttforge-toolchain/venv/lib/python3.10/site-packages/forge/compile.py:293: in forge_compile_from_context
    next_stage = stage_to_func[current_stage](context)
/opt/ttforge-toolchain/venv/lib/python3.10/site-packages/forge/compile.py:671: in generate_initial_graph
    module, module_inputs = convert_to_forge_module(
/opt/ttforge-toolchain/venv/lib/python3.10/site-packages/forge/compile.py:1032: in convert_to_forge_module
    forge_module, dev_types, module_inputs = generate_forge_module(
/opt/ttforge-toolchain/venv/lib/python3.10/site-packages/forge/tvm_to_python.py:2062: in generate_forge_module
    module_writers, flattened_inputs = compile_tvm_to_python(
/opt/ttforge-toolchain/venv/lib/python3.10/site-packages/forge/tvm_to_python.py:2149: in compile_tvm_to_python
    from forge.tvm_calls.forge_compile import load_tvm_graph
/opt/ttforge-toolchain/venv/lib/python3.10/site-packages/forge/tvm_calls/forge_compile.py:36: in <module>
    from forge.tvm_calls.relay.op.forge import verify_tvm_compile, flatten_IO, compile_for_forge, partition_for_forge
_ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ 

    # SPDX-FileCopyrightText:  2024 Tenstorrent AI ULC
    #
    # SPDX-License-Identifier: Apache-2.0
>   from .forge import *
E     File "/opt/ttforge-toolchain/venv/lib/python3.10/site-packages/forge/tvm_calls/relay/op/forge.py", line 19
E       from tvm.relay.dataflow_pattern import *from .reportify import dump_graph
E                                               ^^^^
E   SyntaxError: invalid syntax

/opt/ttforge-toolchain/venv/lib/python3.10/site-packages/forge/tvm_calls/relay/op/__init__.py:4: SyntaxError

Check failure on line 150 in forge/test/mlir/operators/eltwise_binary/test_eltwise_binary.py

See this annotation in the file changed.

@github-actions github-actions / TT-Forge-FE Tests

test_eltwise_binary.test_greater[shape_x3-shape_y3] 

File "/opt/ttforge-toolchain/venv/lib/python3.10/site-packages/forge/tvm_calls/relay/op/forge.py", line 19
    from tvm.relay.dataflow_pattern import *from .reportify import dump_graph
                                            ^^^^
SyntaxError: invalid syntax
Raw output 
shape_x = (1, 128, 14, 14), shape_y = (1, 128, 14, 14)

    @pytest.mark.parametrize(
        "shape_x, shape_y",
        [
            ((1, 128, 28, 28), (1, 128, 28, 28)),
            ((1, 64, 28, 28), (1, 64, 28, 28)),
            ((1, 256, 28, 28), (1, 256, 28, 28)),
            ((1, 128, 14, 14), (1, 128, 14, 14)),
            ((1, 128, 56, 56), (1, 128, 56, 56)),
            ((1, 32, 64, 64), (1, 32, 64, 64)),
            ((1, 512, 7, 7), (1, 512, 7, 7)),
            ((1, 32, 32, 32), (1, 32, 32, 32)),
        ],
    )
    @pytest.mark.push
    def test_greater(shape_x, shape_y):
        class Greater(nn.Module):
            def __init__(self):
                super().__init__()
    
            def forward(self, x, y):
                return torch.greater(x, y)
    
        x = torch.rand(shape_x)
        y = torch.rand(shape_y)
    
        inputs = [x, y]
    
        framework_model = Greater()
>       compiled_model = forge.compile(framework_model, sample_inputs=inputs)

forge/test/mlir/operators/eltwise_binary/test_eltwise_binary.py:150: 
_ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ 
/opt/ttforge-toolchain/venv/lib/python3.10/site-packages/forge/compile.py:251: in compile_main
    return forge_compile_from_context(compile_context)
/opt/ttforge-toolchain/venv/lib/python3.10/site-packages/forge/compile.py:293: in forge_compile_from_context
    next_stage = stage_to_func[current_stage](context)
/opt/ttforge-toolchain/venv/lib/python3.10/site-packages/forge/compile.py:671: in generate_initial_graph
    module, module_inputs = convert_to_forge_module(
/opt/ttforge-toolchain/venv/lib/python3.10/site-packages/forge/compile.py:1032: in convert_to_forge_module
    forge_module, dev_types, module_inputs = generate_forge_module(
/opt/ttforge-toolchain/venv/lib/python3.10/site-packages/forge/tvm_to_python.py:2062: in generate_forge_module
    module_writers, flattened_inputs = compile_tvm_to_python(
/opt/ttforge-toolchain/venv/lib/python3.10/site-packages/forge/tvm_to_python.py:2149: in compile_tvm_to_python
    from forge.tvm_calls.forge_compile import load_tvm_graph
/opt/ttforge-toolchain/venv/lib/python3.10/site-packages/forge/tvm_calls/forge_compile.py:36: in <module>
    from forge.tvm_calls.relay.op.forge import verify_tvm_compile, flatten_IO, compile_for_forge, partition_for_forge
_ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ 

    # SPDX-FileCopyrightText:  2024 Tenstorrent AI ULC
    #
    # SPDX-License-Identifier: Apache-2.0
>   from .forge import *
E     File "/opt/ttforge-toolchain/venv/lib/python3.10/site-packages/forge/tvm_calls/relay/op/forge.py", line 19
E       from tvm.relay.dataflow_pattern import *from .reportify import dump_graph
E                                               ^^^^
E   SyntaxError: invalid syntax

/opt/ttforge-toolchain/venv/lib/python3.10/site-packages/forge/tvm_calls/relay/op/__init__.py:4: SyntaxError

Check failure on line 150 in forge/test/mlir/operators/eltwise_binary/test_eltwise_binary.py

See this annotation in the file changed.

@github-actions github-actions / TT-Forge-FE Tests

test_eltwise_binary.test_greater[shape_x5-shape_y5] 

File "/opt/ttforge-toolchain/venv/lib/python3.10/site-packages/forge/tvm_calls/relay/op/forge.py", line 19
    from tvm.relay.dataflow_pattern import *from .reportify import dump_graph
                                            ^^^^
SyntaxError: invalid syntax
Raw output 
shape_x = (1, 32, 64, 64), shape_y = (1, 32, 64, 64)

    @pytest.mark.parametrize(
        "shape_x, shape_y",
        [
            ((1, 128, 28, 28), (1, 128, 28, 28)),
            ((1, 64, 28, 28), (1, 64, 28, 28)),
            ((1, 256, 28, 28), (1, 256, 28, 28)),
            ((1, 128, 14, 14), (1, 128, 14, 14)),
            ((1, 128, 56, 56), (1, 128, 56, 56)),
            ((1, 32, 64, 64), (1, 32, 64, 64)),
            ((1, 512, 7, 7), (1, 512, 7, 7)),
            ((1, 32, 32, 32), (1, 32, 32, 32)),
        ],
    )
    @pytest.mark.push
    def test_greater(shape_x, shape_y):
        class Greater(nn.Module):
            def __init__(self):
                super().__init__()
    
            def forward(self, x, y):
                return torch.greater(x, y)
    
        x = torch.rand(shape_x)
        y = torch.rand(shape_y)
    
        inputs = [x, y]
    
        framework_model = Greater()
>       compiled_model = forge.compile(framework_model, sample_inputs=inputs)

forge/test/mlir/operators/eltwise_binary/test_eltwise_binary.py:150: 
_ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ 
/opt/ttforge-toolchain/venv/lib/python3.10/site-packages/forge/compile.py:251: in compile_main
    return forge_compile_from_context(compile_context)
/opt/ttforge-toolchain/venv/lib/python3.10/site-packages/forge/compile.py:293: in forge_compile_from_context
    next_stage = stage_to_func[current_stage](context)
/opt/ttforge-toolchain/venv/lib/python3.10/site-packages/forge/compile.py:671: in generate_initial_graph
    module, module_inputs = convert_to_forge_module(
/opt/ttforge-toolchain/venv/lib/python3.10/site-packages/forge/compile.py:1032: in convert_to_forge_module
    forge_module, dev_types, module_inputs = generate_forge_module(
/opt/ttforge-toolchain/venv/lib/python3.10/site-packages/forge/tvm_to_python.py:2062: in generate_forge_module
    module_writers, flattened_inputs = compile_tvm_to_python(
/opt/ttforge-toolchain/venv/lib/python3.10/site-packages/forge/tvm_to_python.py:2149: in compile_tvm_to_python
    from forge.tvm_calls.forge_compile import load_tvm_graph
/opt/ttforge-toolchain/venv/lib/python3.10/site-packages/forge/tvm_calls/forge_compile.py:36: in <module>
    from forge.tvm_calls.relay.op.forge import verify_tvm_compile, flatten_IO, compile_for_forge, partition_for_forge
_ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ 

    # SPDX-FileCopyrightText:  2024 Tenstorrent AI ULC
    #
    # SPDX-License-Identifier: Apache-2.0
>   from .forge import *
E     File "/opt/ttforge-toolchain/venv/lib/python3.10/site-packages/forge/tvm_calls/relay/op/forge.py", line 19
E       from tvm.relay.dataflow_pattern import *from .reportify import dump_graph
E                                               ^^^^
E   SyntaxError: invalid syntax

/opt/ttforge-toolchain/venv/lib/python3.10/site-packages/forge/tvm_calls/relay/op/__init__.py:4: SyntaxError

Check failure on line 150 in forge/test/mlir/operators/eltwise_binary/test_eltwise_binary.py

See this annotation in the file changed.

@github-actions github-actions / TT-Forge-FE Tests

test_eltwise_binary.test_greater[shape_x7-shape_y7] 

File "/opt/ttforge-toolchain/venv/lib/python3.10/site-packages/forge/tvm_calls/relay/op/forge.py", line 19
    from tvm.relay.dataflow_pattern import *from .reportify import dump_graph
                                            ^^^^
SyntaxError: invalid syntax
Raw output 
shape_x = (1, 32, 32, 32), shape_y = (1, 32, 32, 32)

    @pytest.mark.parametrize(
        "shape_x, shape_y",
        [
            ((1, 128, 28, 28), (1, 128, 28, 28)),
            ((1, 64, 28, 28), (1, 64, 28, 28)),
            ((1, 256, 28, 28), (1, 256, 28, 28)),
            ((1, 128, 14, 14), (1, 128, 14, 14)),
            ((1, 128, 56, 56), (1, 128, 56, 56)),
            ((1, 32, 64, 64), (1, 32, 64, 64)),
            ((1, 512, 7, 7), (1, 512, 7, 7)),
            ((1, 32, 32, 32), (1, 32, 32, 32)),
        ],
    )
    @pytest.mark.push
    def test_greater(shape_x, shape_y):
        class Greater(nn.Module):
            def __init__(self):
                super().__init__()
    
            def forward(self, x, y):
                return torch.greater(x, y)
    
        x = torch.rand(shape_x)
        y = torch.rand(shape_y)
    
        inputs = [x, y]
    
        framework_model = Greater()
>       compiled_model = forge.compile(framework_model, sample_inputs=inputs)

forge/test/mlir/operators/eltwise_binary/test_eltwise_binary.py:150: 
_ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ 
/opt/ttforge-toolchain/venv/lib/python3.10/site-packages/forge/compile.py:251: in compile_main
    return forge_compile_from_context(compile_context)
/opt/ttforge-toolchain/venv/lib/python3.10/site-packages/forge/compile.py:293: in forge_compile_from_context
    next_stage = stage_to_func[current_stage](context)
/opt/ttforge-toolchain/venv/lib/python3.10/site-packages/forge/compile.py:671: in generate_initial_graph
    module, module_inputs = convert_to_forge_module(
/opt/ttforge-toolchain/venv/lib/python3.10/site-packages/forge/compile.py:1032: in convert_to_forge_module
    forge_module, dev_types, module_inputs = generate_forge_module(
/opt/ttforge-toolchain/venv/lib/python3.10/site-packages/forge/tvm_to_python.py:2062: in generate_forge_module
    module_writers, flattened_inputs = compile_tvm_to_python(
/opt/ttforge-toolchain/venv/lib/python3.10/site-packages/forge/tvm_to_python.py:2149: in compile_tvm_to_python
    from forge.tvm_calls.forge_compile import load_tvm_graph
/opt/ttforge-toolchain/venv/lib/python3.10/site-packages/forge/tvm_calls/forge_compile.py:36: in <module>
    from forge.tvm_calls.relay.op.forge import verify_tvm_compile, flatten_IO, compile_for_forge, partition_for_forge
_ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ 

    # SPDX-FileCopyrightText:  2024 Tenstorrent AI ULC
    #
    # SPDX-License-Identifier: Apache-2.0
>   from .forge import *
E     File "/opt/ttforge-toolchain/venv/lib/python3.10/site-packages/forge/tvm_calls/relay/op/forge.py", line 19
E       from tvm.relay.dataflow_pattern import *from .reportify import dump_graph
E                                               ^^^^
E   SyntaxError: invalid syntax

/opt/ttforge-toolchain/venv/lib/python3.10/site-packages/forge/tvm_calls/relay/op/__init__.py:4: SyntaxError

Check failure on line 183 in forge/test/mlir/operators/eltwise_binary/test_eltwise_binary.py

See this annotation in the file changed.

@github-actions github-actions / TT-Forge-FE Tests

test_eltwise_binary.test_not_equal[shape_x1-shape_y1] 

File "/opt/ttforge-toolchain/venv/lib/python3.10/site-packages/forge/tvm_calls/relay/op/forge.py", line 19
    from tvm.relay.dataflow_pattern import *from .reportify import dump_graph
                                            ^^^^
SyntaxError: invalid syntax
Raw output 
shape_x = (1, 64, 28, 28), shape_y = (1, 64, 28, 28)

    @pytest.mark.parametrize(
        "shape_x, shape_y",
        [
            ((1, 128, 28, 28), (1, 128, 28, 28)),
            ((1, 64, 28, 28), (1, 64, 28, 28)),
            ((1, 256, 28, 28), (1, 256, 28, 28)),
            ((1, 128, 14, 14), (1, 128, 14, 14)),
            ((1, 128, 56, 56), (1, 128, 56, 56)),
            ((1, 32, 64, 64), (1, 32, 64, 64)),
            ((1, 512, 7, 7), (1, 512, 7, 7)),
            ((1, 32, 32, 32), (1, 32, 32, 32)),
        ],
    )
    @pytest.mark.push
    def test_not_equal(shape_x, shape_y):
        class NotEqual(nn.Module):
            def __init__(self):
                super().__init__()
    
            def forward(self, x, y):
                return torch.ne(x, y)
    
        x = torch.rand(shape_x)
        y = torch.rand(shape_y)
    
        inputs = [x, y]
    
        framework_model = NotEqual()
>       compiled_model = forge.compile(framework_model, sample_inputs=inputs)

forge/test/mlir/operators/eltwise_binary/test_eltwise_binary.py:183: 
_ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ 
/opt/ttforge-toolchain/venv/lib/python3.10/site-packages/forge/compile.py:251: in compile_main
    return forge_compile_from_context(compile_context)
/opt/ttforge-toolchain/venv/lib/python3.10/site-packages/forge/compile.py:293: in forge_compile_from_context
    next_stage = stage_to_func[current_stage](context)
/opt/ttforge-toolchain/venv/lib/python3.10/site-packages/forge/compile.py:671: in generate_initial_graph
    module, module_inputs = convert_to_forge_module(
/opt/ttforge-toolchain/venv/lib/python3.10/site-packages/forge/compile.py:1032: in convert_to_forge_module
    forge_module, dev_types, module_inputs = generate_forge_module(
/opt/ttforge-toolchain/venv/lib/python3.10/site-packages/forge/tvm_to_python.py:2062: in generate_forge_module
    module_writers, flattened_inputs = compile_tvm_to_python(
/opt/ttforge-toolchain/venv/lib/python3.10/site-packages/forge/tvm_to_python.py:2149: in compile_tvm_to_python
    from forge.tvm_calls.forge_compile import load_tvm_graph
/opt/ttforge-toolchain/venv/lib/python3.10/site-packages/forge/tvm_calls/forge_compile.py:36: in <module>
    from forge.tvm_calls.relay.op.forge import verify_tvm_compile, flatten_IO, compile_for_forge, partition_for_forge
_ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ 

    # SPDX-FileCopyrightText:  2024 Tenstorrent AI ULC
    #
    # SPDX-License-Identifier: Apache-2.0
>   from .forge import *
E     File "/opt/ttforge-toolchain/venv/lib/python3.10/site-packages/forge/tvm_calls/relay/op/forge.py", line 19
E       from tvm.relay.dataflow_pattern import *from .reportify import dump_graph
E                                               ^^^^
E   SyntaxError: invalid syntax

/opt/ttforge-toolchain/venv/lib/python3.10/site-packages/forge/tvm_calls/relay/op/__init__.py:4: SyntaxError

Check failure on line 183 in forge/test/mlir/operators/eltwise_binary/test_eltwise_binary.py

See this annotation in the file changed.

@github-actions github-actions / TT-Forge-FE Tests

test_eltwise_binary.test_not_equal[shape_x3-shape_y3] 

File "/opt/ttforge-toolchain/venv/lib/python3.10/site-packages/forge/tvm_calls/relay/op/forge.py", line 19
    from tvm.relay.dataflow_pattern import *from .reportify import dump_graph
                                            ^^^^
SyntaxError: invalid syntax
Raw output 
shape_x = (1, 128, 14, 14), shape_y = (1, 128, 14, 14)

    @pytest.mark.parametrize(
        "shape_x, shape_y",
        [
            ((1, 128, 28, 28), (1, 128, 28, 28)),
            ((1, 64, 28, 28), (1, 64, 28, 28)),
            ((1, 256, 28, 28), (1, 256, 28, 28)),
            ((1, 128, 14, 14), (1, 128, 14, 14)),
            ((1, 128, 56, 56), (1, 128, 56, 56)),
            ((1, 32, 64, 64), (1, 32, 64, 64)),
            ((1, 512, 7, 7), (1, 512, 7, 7)),
            ((1, 32, 32, 32), (1, 32, 32, 32)),
        ],
    )
    @pytest.mark.push
    def test_not_equal(shape_x, shape_y):
        class NotEqual(nn.Module):
            def __init__(self):
                super().__init__()
    
            def forward(self, x, y):
                return torch.ne(x, y)
    
        x = torch.rand(shape_x)
        y = torch.rand(shape_y)
    
        inputs = [x, y]
    
        framework_model = NotEqual()
>       compiled_model = forge.compile(framework_model, sample_inputs=inputs)

forge/test/mlir/operators/eltwise_binary/test_eltwise_binary.py:183: 
_ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ 
/opt/ttforge-toolchain/venv/lib/python3.10/site-packages/forge/compile.py:251: in compile_main
    return forge_compile_from_context(compile_context)
/opt/ttforge-toolchain/venv/lib/python3.10/site-packages/forge/compile.py:293: in forge_compile_from_context
    next_stage = stage_to_func[current_stage](context)
/opt/ttforge-toolchain/venv/lib/python3.10/site-packages/forge/compile.py:671: in generate_initial_graph
    module, module_inputs = convert_to_forge_module(
/opt/ttforge-toolchain/venv/lib/python3.10/site-packages/forge/compile.py:1032: in convert_to_forge_module
    forge_module, dev_types, module_inputs = generate_forge_module(
/opt/ttforge-toolchain/venv/lib/python3.10/site-packages/forge/tvm_to_python.py:2062: in generate_forge_module
    module_writers, flattened_inputs = compile_tvm_to_python(
/opt/ttforge-toolchain/venv/lib/python3.10/site-packages/forge/tvm_to_python.py:2149: in compile_tvm_to_python
    from forge.tvm_calls.forge_compile import load_tvm_graph
/opt/ttforge-toolchain/venv/lib/python3.10/site-packages/forge/tvm_calls/forge_compile.py:36: in <module>
    from forge.tvm_calls.relay.op.forge import verify_tvm_compile, flatten_IO, compile_for_forge, partition_for_forge
_ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ 

    # SPDX-FileCopyrightText:  2024 Tenstorrent AI ULC
    #
    # SPDX-License-Identifier: Apache-2.0
>   from .forge import *
E     File "/opt/ttforge-toolchain/venv/lib/python3.10/site-packages/forge/tvm_calls/relay/op/forge.py", line 19
E       from tvm.relay.dataflow_pattern import *from .reportify import dump_graph
E                                               ^^^^
E   SyntaxError: invalid syntax

/opt/ttforge-toolchain/venv/lib/python3.10/site-packages/forge/tvm_calls/relay/op/__init__.py:4: SyntaxError

Check failure on line 183 in forge/test/mlir/operators/eltwise_binary/test_eltwise_binary.py

See this annotation in the file changed.

@github-actions github-actions / TT-Forge-FE Tests

test_eltwise_binary.test_not_equal[shape_x5-shape_y5] 

File "/opt/ttforge-toolchain/venv/lib/python3.10/site-packages/forge/tvm_calls/relay/op/forge.py", line 19
    from tvm.relay.dataflow_pattern import *from .reportify import dump_graph
                                            ^^^^
SyntaxError: invalid syntax
Raw output 
shape_x = (1, 32, 64, 64), shape_y = (1, 32, 64, 64)

    @pytest.mark.parametrize(
        "shape_x, shape_y",
        [
            ((1, 128, 28, 28), (1, 128, 28, 28)),
            ((1, 64, 28, 28), (1, 64, 28, 28)),
            ((1, 256, 28, 28), (1, 256, 28, 28)),
            ((1, 128, 14, 14), (1, 128, 14, 14)),
            ((1, 128, 56, 56), (1, 128, 56, 56)),
            ((1, 32, 64, 64), (1, 32, 64, 64)),
            ((1, 512, 7, 7), (1, 512, 7, 7)),
            ((1, 32, 32, 32), (1, 32, 32, 32)),
        ],
    )
    @pytest.mark.push
    def test_not_equal(shape_x, shape_y):
        class NotEqual(nn.Module):
            def __init__(self):
                super().__init__()
    
            def forward(self, x, y):
                return torch.ne(x, y)
    
        x = torch.rand(shape_x)
        y = torch.rand(shape_y)
    
        inputs = [x, y]
    
        framework_model = NotEqual()
>       compiled_model = forge.compile(framework_model, sample_inputs=inputs)

forge/test/mlir/operators/eltwise_binary/test_eltwise_binary.py:183: 
_ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ 
/opt/ttforge-toolchain/venv/lib/python3.10/site-packages/forge/compile.py:251: in compile_main
    return forge_compile_from_context(compile_context)
/opt/ttforge-toolchain/venv/lib/python3.10/site-packages/forge/compile.py:293: in forge_compile_from_context
    next_stage = stage_to_func[current_stage](context)
/opt/ttforge-toolchain/venv/lib/python3.10/site-packages/forge/compile.py:671: in generate_initial_graph
    module, module_inputs = convert_to_forge_module(
/opt/ttforge-toolchain/venv/lib/python3.10/site-packages/forge/compile.py:1032: in convert_to_forge_module
    forge_module, dev_types, module_inputs = generate_forge_module(
/opt/ttforge-toolchain/venv/lib/python3.10/site-packages/forge/tvm_to_python.py:2062: in generate_forge_module
    module_writers, flattened_inputs = compile_tvm_to_python(
/opt/ttforge-toolchain/venv/lib/python3.10/site-packages/forge/tvm_to_python.py:2149: in compile_tvm_to_python
    from forge.tvm_calls.forge_compile import load_tvm_graph
/opt/ttforge-toolchain/venv/lib/python3.10/site-packages/forge/tvm_calls/forge_compile.py:36: in <module>
    from forge.tvm_calls.relay.op.forge import verify_tvm_compile, flatten_IO, compile_for_forge, partition_for_forge
_ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ 

    # SPDX-FileCopyrightText:  2024 Tenstorrent AI ULC
    #
    # SPDX-License-Identifier: Apache-2.0
>   from .forge import *
E     File "/opt/ttforge-toolchain/venv/lib/python3.10/site-packages/forge/tvm_calls/relay/op/forge.py", line 19
E       from tvm.relay.dataflow_pattern import *from .reportify import dump_graph
E                                               ^^^^
E   SyntaxError: invalid syntax

/opt/ttforge-toolchain/venv/lib/python3.10/site-packages/forge/tvm_calls/relay/op/__init__.py:4: SyntaxError

Check failure on line 183 in forge/test/mlir/operators/eltwise_binary/test_eltwise_binary.py

See this annotation in the file changed.

@github-actions github-actions / TT-Forge-FE Tests

test_eltwise_binary.test_not_equal[shape_x7-shape_y7] 

File "/opt/ttforge-toolchain/venv/lib/python3.10/site-packages/forge/tvm_calls/relay/op/forge.py", line 19
    from tvm.relay.dataflow_pattern import *from .reportify import dump_graph
                                            ^^^^
SyntaxError: invalid syntax
Raw output 
shape_x = (1, 32, 32, 32), shape_y = (1, 32, 32, 32)

    @pytest.mark.parametrize(
        "shape_x, shape_y",
        [
            ((1, 128, 28, 28), (1, 128, 28, 28)),
            ((1, 64, 28, 28), (1, 64, 28, 28)),
            ((1, 256, 28, 28), (1, 256, 28, 28)),
            ((1, 128, 14, 14), (1, 128, 14, 14)),
            ((1, 128, 56, 56), (1, 128, 56, 56)),
            ((1, 32, 64, 64), (1, 32, 64, 64)),
            ((1, 512, 7, 7), (1, 512, 7, 7)),
            ((1, 32, 32, 32), (1, 32, 32, 32)),
        ],
    )
    @pytest.mark.push
    def test_not_equal(shape_x, shape_y):
        class NotEqual(nn.Module):
            def __init__(self):
                super().__init__()
    
            def forward(self, x, y):
                return torch.ne(x, y)
    
        x = torch.rand(shape_x)
        y = torch.rand(shape_y)
    
        inputs = [x, y]
    
        framework_model = NotEqual()
>       compiled_model = forge.compile(framework_model, sample_inputs=inputs)

forge/test/mlir/operators/eltwise_binary/test_eltwise_binary.py:183: 
_ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ 
/opt/ttforge-toolchain/venv/lib/python3.10/site-packages/forge/compile.py:251: in compile_main
    return forge_compile_from_context(compile_context)
/opt/ttforge-toolchain/venv/lib/python3.10/site-packages/forge/compile.py:293: in forge_compile_from_context
    next_stage = stage_to_func[current_stage](context)
/opt/ttforge-toolchain/venv/lib/python3.10/site-packages/forge/compile.py:671: in generate_initial_graph
    module, module_inputs = convert_to_forge_module(
/opt/ttforge-toolchain/venv/lib/python3.10/site-packages/forge/compile.py:1032: in convert_to_forge_module
    forge_module, dev_types, module_inputs = generate_forge_module(
/opt/ttforge-toolchain/venv/lib/python3.10/site-packages/forge/tvm_to_python.py:2062: in generate_forge_module
    module_writers, flattened_inputs = compile_tvm_to_python(
/opt/ttforge-toolchain/venv/lib/python3.10/site-packages/forge/tvm_to_python.py:2149: in compile_tvm_to_python
    from forge.tvm_calls.forge_compile import load_tvm_graph
/opt/ttforge-toolchain/venv/lib/python3.10/site-packages/forge/tvm_calls/forge_compile.py:36: in <module>
    from forge.tvm_calls.relay.op.forge import verify_tvm_compile, flatten_IO, compile_for_forge, partition_for_forge
_ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ 

    # SPDX-FileCopyrightText:  2024 Tenstorrent AI ULC
    #
    # SPDX-License-Identifier: Apache-2.0
>   from .forge import *
E     File "/opt/ttforge-toolchain/venv/lib/python3.10/site-packages/forge/tvm_calls/relay/op/forge.py", line 19
E       from tvm.relay.dataflow_pattern import *from .reportify import dump_graph
E                                               ^^^^
E   SyntaxError: invalid syntax

/opt/ttforge-toolchain/venv/lib/python3.10/site-packages/forge/tvm_calls/relay/op/__init__.py:4: SyntaxError

Check failure on line 232 in forge/test/mlir/operators/eltwise_binary/test_eltwise_binary.py

See this annotation in the file changed.

@github-actions github-actions / TT-Forge-FE Tests

test_eltwise_binary.test_equal[shape0] 

File "/opt/ttforge-toolchain/venv/lib/python3.10/site-packages/forge/tvm_calls/relay/op/forge.py", line 19
    from tvm.relay.dataflow_pattern import *from .reportify import dump_graph
                                            ^^^^
SyntaxError: invalid syntax
Raw output 
shape = (1, 128, 28, 28)

    @pytest.mark.parametrize(
        "shape",
        [
            (1, 128, 28, 28),
            (1, 64, 28, 28),
            (1, 256, 28, 28),
            (1, 128, 14, 14),
            (1, 128, 56, 56),
            (1, 32, 64, 64),
            (1, 512, 7, 7),
            (1, 32, 32, 32),
            (128, 28, 28),
            (64, 28, 28),
            (256, 28, 28),
            (128, 14, 14),
            (128, 56, 56),
            (32, 64, 64),
            (512, 7, 7),
            (32, 32, 32),
            (128, 28),
            (64, 28),
            (256, 28),
            (128, 14),
            (128, 56),
            (32, 64),
            (512, 7),
            (32, 32),
        ],
    )
    @pytest.mark.push
    def test_equal(shape):
        class Equal(nn.Module):
            def __init__(self):
                super().__init__()
    
            def forward(self, x, y):
                return torch.eq(x, y)
    
        x = torch.rand(shape)
        y = x * 2.0
    
        inputs = [x, y]
    
        framework_model = Equal()
>       compiled_model = forge.compile(framework_model, sample_inputs=inputs)

forge/test/mlir/operators/eltwise_binary/test_eltwise_binary.py:232: 
_ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ 
/opt/ttforge-toolchain/venv/lib/python3.10/site-packages/forge/compile.py:251: in compile_main
    return forge_compile_from_context(compile_context)
/opt/ttforge-toolchain/venv/lib/python3.10/site-packages/forge/compile.py:293: in forge_compile_from_context
    next_stage = stage_to_func[current_stage](context)
/opt/ttforge-toolchain/venv/lib/python3.10/site-packages/forge/compile.py:671: in generate_initial_graph
    module, module_inputs = convert_to_forge_module(
/opt/ttforge-toolchain/venv/lib/python3.10/site-packages/forge/compile.py:1032: in convert_to_forge_module
    forge_module, dev_types, module_inputs = generate_forge_module(
/opt/ttforge-toolchain/venv/lib/python3.10/site-packages/forge/tvm_to_python.py:2062: in generate_forge_module
    module_writers, flattened_inputs = compile_tvm_to_python(
/opt/ttforge-toolchain/venv/lib/python3.10/site-packages/forge/tvm_to_python.py:2149: in compile_tvm_to_python
    from forge.tvm_calls.forge_compile import load_tvm_graph
/opt/ttforge-toolchain/venv/lib/python3.10/site-packages/forge/tvm_calls/forge_compile.py:36: in <module>
    from forge.tvm_calls.relay.op.forge import verify_tvm_compile, flatten_IO, compile_for_forge, partition_for_forge
_ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ 

    # SPDX-FileCopyrightText:  2024 Tenstorrent AI ULC
    #
    # SPDX-License-Identifier: Apache-2.0
>   from .forge import *
E     File "/opt/ttforge-toolchain/venv/lib/python3.10/site-packages/forge/tvm_calls/relay/op/forge.py", line 19
E       from tvm.relay.dataflow_pattern import *from .reportify import dump_graph
E                                               ^^^^
E   SyntaxError: invalid syntax

/opt/ttforge-toolchain/venv/lib/python3.10/site-packages/forge/tvm_calls/relay/op/__init__.py:4: SyntaxError

Check failure on line 232 in forge/test/mlir/operators/eltwise_binary/test_eltwise_binary.py

See this annotation in the file changed.

@github-actions github-actions / TT-Forge-FE Tests

test_eltwise_binary.test_equal[shape2] 

File "/opt/ttforge-toolchain/venv/lib/python3.10/site-packages/forge/tvm_calls/relay/op/forge.py", line 19
    from tvm.relay.dataflow_pattern import *from .reportify import dump_graph
                                            ^^^^
SyntaxError: invalid syntax
Raw output 
shape = (1, 256, 28, 28)

    @pytest.mark.parametrize(
        "shape",
        [
            (1, 128, 28, 28),
            (1, 64, 28, 28),
            (1, 256, 28, 28),
            (1, 128, 14, 14),
            (1, 128, 56, 56),
            (1, 32, 64, 64),
            (1, 512, 7, 7),
            (1, 32, 32, 32),
            (128, 28, 28),
            (64, 28, 28),
            (256, 28, 28),
            (128, 14, 14),
            (128, 56, 56),
            (32, 64, 64),
            (512, 7, 7),
            (32, 32, 32),
            (128, 28),
            (64, 28),
            (256, 28),
            (128, 14),
            (128, 56),
            (32, 64),
            (512, 7),
            (32, 32),
        ],
    )
    @pytest.mark.push
    def test_equal(shape):
        class Equal(nn.Module):
            def __init__(self):
                super().__init__()
    
            def forward(self, x, y):
                return torch.eq(x, y)
    
        x = torch.rand(shape)
        y = x * 2.0
    
        inputs = [x, y]
    
        framework_model = Equal()
>       compiled_model = forge.compile(framework_model, sample_inputs=inputs)

forge/test/mlir/operators/eltwise_binary/test_eltwise_binary.py:232: 
_ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ 
/opt/ttforge-toolchain/venv/lib/python3.10/site-packages/forge/compile.py:251: in compile_main
    return forge_compile_from_context(compile_context)
/opt/ttforge-toolchain/venv/lib/python3.10/site-packages/forge/compile.py:293: in forge_compile_from_context
    next_stage = stage_to_func[current_stage](context)
/opt/ttforge-toolchain/venv/lib/python3.10/site-packages/forge/compile.py:671: in generate_initial_graph
    module, module_inputs = convert_to_forge_module(
/opt/ttforge-toolchain/venv/lib/python3.10/site-packages/forge/compile.py:1032: in convert_to_forge_module
    forge_module, dev_types, module_inputs = generate_forge_module(
/opt/ttforge-toolchain/venv/lib/python3.10/site-packages/forge/tvm_to_python.py:2062: in generate_forge_module
    module_writers, flattened_inputs = compile_tvm_to_python(
/opt/ttforge-toolchain/venv/lib/python3.10/site-packages/forge/tvm_to_python.py:2149: in compile_tvm_to_python
    from forge.tvm_calls.forge_compile import load_tvm_graph
/opt/ttforge-toolchain/venv/lib/python3.10/site-packages/forge/tvm_calls/forge_compile.py:36: in <module>
    from forge.tvm_calls.relay.op.forge import verify_tvm_compile, flatten_IO, compile_for_forge, partition_for_forge
_ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ 

    # SPDX-FileCopyrightText:  2024 Tenstorrent AI ULC
    #
    # SPDX-License-Identifier: Apache-2.0
>   from .forge import *
E     File "/opt/ttforge-toolchain/venv/lib/python3.10/site-packages/forge/tvm_calls/relay/op/forge.py", line 19
E       from tvm.relay.dataflow_pattern import *from .reportify import dump_graph
E                                               ^^^^
E   SyntaxError: invalid syntax

/opt/ttforge-toolchain/venv/lib/python3.10/site-packages/forge/tvm_calls/relay/op/__init__.py:4: SyntaxError

Check failure on line 232 in forge/test/mlir/operators/eltwise_binary/test_eltwise_binary.py

See this annotation in the file changed.

@github-actions github-actions / TT-Forge-FE Tests

test_eltwise_binary.test_equal[shape4] 

File "/opt/ttforge-toolchain/venv/lib/python3.10/site-packages/forge/tvm_calls/relay/op/forge.py", line 19
    from tvm.relay.dataflow_pattern import *from .reportify import dump_graph
                                            ^^^^
SyntaxError: invalid syntax
Raw output 
shape = (1, 128, 56, 56)

    @pytest.mark.parametrize(
        "shape",
        [
            (1, 128, 28, 28),
            (1, 64, 28, 28),
            (1, 256, 28, 28),
            (1, 128, 14, 14),
            (1, 128, 56, 56),
            (1, 32, 64, 64),
            (1, 512, 7, 7),
            (1, 32, 32, 32),
            (128, 28, 28),
            (64, 28, 28),
            (256, 28, 28),
            (128, 14, 14),
            (128, 56, 56),
            (32, 64, 64),
            (512, 7, 7),
            (32, 32, 32),
            (128, 28),
            (64, 28),
            (256, 28),
            (128, 14),
            (128, 56),
            (32, 64),
            (512, 7),
            (32, 32),
        ],
    )
    @pytest.mark.push
    def test_equal(shape):
        class Equal(nn.Module):
            def __init__(self):
                super().__init__()
    
            def forward(self, x, y):
                return torch.eq(x, y)
    
        x = torch.rand(shape)
        y = x * 2.0
    
        inputs = [x, y]
    
        framework_model = Equal()
>       compiled_model = forge.compile(framework_model, sample_inputs=inputs)

forge/test/mlir/operators/eltwise_binary/test_eltwise_binary.py:232: 
_ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ 
/opt/ttforge-toolchain/venv/lib/python3.10/site-packages/forge/compile.py:251: in compile_main
    return forge_compile_from_context(compile_context)
/opt/ttforge-toolchain/venv/lib/python3.10/site-packages/forge/compile.py:293: in forge_compile_from_context
    next_stage = stage_to_func[current_stage](context)
/opt/ttforge-toolchain/venv/lib/python3.10/site-packages/forge/compile.py:671: in generate_initial_graph
    module, module_inputs = convert_to_forge_module(
/opt/ttforge-toolchain/venv/lib/python3.10/site-packages/forge/compile.py:1032: in convert_to_forge_module
    forge_module, dev_types, module_inputs = generate_forge_module(
/opt/ttforge-toolchain/venv/lib/python3.10/site-packages/forge/tvm_to_python.py:2062: in generate_forge_module
    module_writers, flattened_inputs = compile_tvm_to_python(
/opt/ttforge-toolchain/venv/lib/python3.10/site-packages/forge/tvm_to_python.py:2149: in compile_tvm_to_python
    from forge.tvm_calls.forge_compile import load_tvm_graph
/opt/ttforge-toolchain/venv/lib/python3.10/site-packages/forge/tvm_calls/forge_compile.py:36: in <module>
    from forge.tvm_calls.relay.op.forge import verify_tvm_compile, flatten_IO, compile_for_forge, partition_for_forge
_ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ 

    # SPDX-FileCopyrightText:  2024 Tenstorrent AI ULC
    #
    # SPDX-License-Identifier: Apache-2.0
>   from .forge import *
E     File "/opt/ttforge-toolchain/venv/lib/python3.10/site-packages/forge/tvm_calls/relay/op/forge.py", line 19
E       from tvm.relay.dataflow_pattern import *from .reportify import dump_graph
E                                               ^^^^
E   SyntaxError: invalid syntax

/opt/ttforge-toolchain/venv/lib/python3.10/site-packages/forge/tvm_calls/relay/op/__init__.py:4: SyntaxError

Check failure on line 232 in forge/test/mlir/operators/eltwise_binary/test_eltwise_binary.py

See this annotation in the file changed.

@github-actions github-actions / TT-Forge-FE Tests

test_eltwise_binary.test_equal[shape6] 

File "/opt/ttforge-toolchain/venv/lib/python3.10/site-packages/forge/tvm_calls/relay/op/forge.py", line 19
    from tvm.relay.dataflow_pattern import *from .reportify import dump_graph
                                            ^^^^
SyntaxError: invalid syntax
Raw output 
shape = (1, 512, 7, 7)

    @pytest.mark.parametrize(
        "shape",
        [
            (1, 128, 28, 28),
            (1, 64, 28, 28),
            (1, 256, 28, 28),
            (1, 128, 14, 14),
            (1, 128, 56, 56),
            (1, 32, 64, 64),
            (1, 512, 7, 7),
            (1, 32, 32, 32),
            (128, 28, 28),
            (64, 28, 28),
            (256, 28, 28),
            (128, 14, 14),
            (128, 56, 56),
            (32, 64, 64),
            (512, 7, 7),
            (32, 32, 32),
            (128, 28),
            (64, 28),
            (256, 28),
            (128, 14),
            (128, 56),
            (32, 64),
            (512, 7),
            (32, 32),
        ],
    )
    @pytest.mark.push
    def test_equal(shape):
        class Equal(nn.Module):
            def __init__(self):
                super().__init__()
    
            def forward(self, x, y):
                return torch.eq(x, y)
    
        x = torch.rand(shape)
        y = x * 2.0
    
        inputs = [x, y]
    
        framework_model = Equal()
>       compiled_model = forge.compile(framework_model, sample_inputs=inputs)

forge/test/mlir/operators/eltwise_binary/test_eltwise_binary.py:232: 
_ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ 
/opt/ttforge-toolchain/venv/lib/python3.10/site-packages/forge/compile.py:251: in compile_main
    return forge_compile_from_context(compile_context)
/opt/ttforge-toolchain/venv/lib/python3.10/site-packages/forge/compile.py:293: in forge_compile_from_context
    next_stage = stage_to_func[current_stage](context)
/opt/ttforge-toolchain/venv/lib/python3.10/site-packages/forge/compile.py:671: in generate_initial_graph
    module, module_inputs = convert_to_forge_module(
/opt/ttforge-toolchain/venv/lib/python3.10/site-packages/forge/compile.py:1032: in convert_to_forge_module
    forge_module, dev_types, module_inputs = generate_forge_module(
/opt/ttforge-toolchain/venv/lib/python3.10/site-packages/forge/tvm_to_python.py:2062: in generate_forge_module
    module_writers, flattened_inputs = compile_tvm_to_python(
/opt/ttforge-toolchain/venv/lib/python3.10/site-packages/forge/tvm_to_python.py:2149: in compile_tvm_to_python
    from forge.tvm_calls.forge_compile import load_tvm_graph
/opt/ttforge-toolchain/venv/lib/python3.10/site-packages/forge/tvm_calls/forge_compile.py:36: in <module>
    from forge.tvm_calls.relay.op.forge import verify_tvm_compile, flatten_IO, compile_for_forge, partition_for_forge
_ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ 

    # SPDX-FileCopyrightText:  2024 Tenstorrent AI ULC
    #
    # SPDX-License-Identifier: Apache-2.0
>   from .forge import *
E     File "/opt/ttforge-toolchain/venv/lib/python3.10/site-packages/forge/tvm_calls/relay/op/forge.py", line 19
E       from tvm.relay.dataflow_pattern import *from .reportify import dump_graph
E                                               ^^^^
E   SyntaxError: invalid syntax

/opt/ttforge-toolchain/venv/lib/python3.10/site-packages/forge/tvm_calls/relay/op/__init__.py:4: SyntaxError

Check failure on line 232 in forge/test/mlir/operators/eltwise_binary/test_eltwise_binary.py

See this annotation in the file changed.

@github-actions github-actions / TT-Forge-FE Tests

test_eltwise_binary.test_equal[shape8] 

File "/opt/ttforge-toolchain/venv/lib/python3.10/site-packages/forge/tvm_calls/relay/op/forge.py", line 19
    from tvm.relay.dataflow_pattern import *from .reportify import dump_graph
                                            ^^^^
SyntaxError: invalid syntax
Raw output 
shape = (128, 28, 28)

    @pytest.mark.parametrize(
        "shape",
        [
            (1, 128, 28, 28),
            (1, 64, 28, 28),
            (1, 256, 28, 28),
            (1, 128, 14, 14),
            (1, 128, 56, 56),
            (1, 32, 64, 64),
            (1, 512, 7, 7),
            (1, 32, 32, 32),
            (128, 28, 28),
            (64, 28, 28),
            (256, 28, 28),
            (128, 14, 14),
            (128, 56, 56),
            (32, 64, 64),
            (512, 7, 7),
            (32, 32, 32),
            (128, 28),
            (64, 28),
            (256, 28),
            (128, 14),
            (128, 56),
            (32, 64),
            (512, 7),
            (32, 32),
        ],
    )
    @pytest.mark.push
    def test_equal(shape):
        class Equal(nn.Module):
            def __init__(self):
                super().__init__()
    
            def forward(self, x, y):
                return torch.eq(x, y)
    
        x = torch.rand(shape)
        y = x * 2.0
    
        inputs = [x, y]
    
        framework_model = Equal()
>       compiled_model = forge.compile(framework_model, sample_inputs=inputs)

forge/test/mlir/operators/eltwise_binary/test_eltwise_binary.py:232: 
_ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ 
/opt/ttforge-toolchain/venv/lib/python3.10/site-packages/forge/compile.py:251: in compile_main
    return forge_compile_from_context(compile_context)
/opt/ttforge-toolchain/venv/lib/python3.10/site-packages/forge/compile.py:293: in forge_compile_from_context
    next_stage = stage_to_func[current_stage](context)
/opt/ttforge-toolchain/venv/lib/python3.10/site-packages/forge/compile.py:671: in generate_initial_graph
    module, module_inputs = convert_to_forge_module(
/opt/ttforge-toolchain/venv/lib/python3.10/site-packages/forge/compile.py:1032: in convert_to_forge_module
    forge_module, dev_types, module_inputs = generate_forge_module(
/opt/ttforge-toolchain/venv/lib/python3.10/site-packages/forge/tvm_to_python.py:2062: in generate_forge_module
    module_writers, flattened_inputs = compile_tvm_to_python(
/opt/ttforge-toolchain/venv/lib/python3.10/site-packages/forge/tvm_to_python.py:2149: in compile_tvm_to_python
    from forge.tvm_calls.forge_compile import load_tvm_graph
/opt/ttforge-toolchain/venv/lib/python3.10/site-packages/forge/tvm_calls/forge_compile.py:36: in <module>
    from forge.tvm_calls.relay.op.forge import verify_tvm_compile, flatten_IO, compile_for_forge, partition_for_forge
_ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ 

    # SPDX-FileCopyrightText:  2024 Tenstorrent AI ULC
    #
    # SPDX-License-Identifier: Apache-2.0
>   from .forge import *
E     File "/opt/ttforge-toolchain/venv/lib/python3.10/site-packages/forge/tvm_calls/relay/op/forge.py", line 19
E       from tvm.relay.dataflow_pattern import *from .reportify import dump_graph
E                                               ^^^^
E   SyntaxError: invalid syntax

/opt/ttforge-toolchain/venv/lib/python3.10/site-packages/forge/tvm_calls/relay/op/__init__.py:4: SyntaxError

Check failure on line 232 in forge/test/mlir/operators/eltwise_binary/test_eltwise_binary.py

See this annotation in the file changed.

@github-actions github-actions / TT-Forge-FE Tests

test_eltwise_binary.test_equal[shape11] 

File "/opt/ttforge-toolchain/venv/lib/python3.10/site-packages/forge/tvm_calls/relay/op/forge.py", line 19
    from tvm.relay.dataflow_pattern import *from .reportify import dump_graph
                                            ^^^^
SyntaxError: invalid syntax
Raw output 
shape = (128, 14, 14)

    @pytest.mark.parametrize(
        "shape",
        [
            (1, 128, 28, 28),
            (1, 64, 28, 28),
            (1, 256, 28, 28),
            (1, 128, 14, 14),
            (1, 128, 56, 56),
            (1, 32, 64, 64),
            (1, 512, 7, 7),
            (1, 32, 32, 32),
            (128, 28, 28),
            (64, 28, 28),
            (256, 28, 28),
            (128, 14, 14),
            (128, 56, 56),
            (32, 64, 64),
            (512, 7, 7),
            (32, 32, 32),
            (128, 28),
            (64, 28),
            (256, 28),
            (128, 14),
            (128, 56),
            (32, 64),
            (512, 7),
            (32, 32),
        ],
    )
    @pytest.mark.push
    def test_equal(shape):
        class Equal(nn.Module):
            def __init__(self):
                super().__init__()
    
            def forward(self, x, y):
                return torch.eq(x, y)
    
        x = torch.rand(shape)
        y = x * 2.0
    
        inputs = [x, y]
    
        framework_model = Equal()
>       compiled_model = forge.compile(framework_model, sample_inputs=inputs)

forge/test/mlir/operators/eltwise_binary/test_eltwise_binary.py:232: 
_ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ 
/opt/ttforge-toolchain/venv/lib/python3.10/site-packages/forge/compile.py:251: in compile_main
    return forge_compile_from_context(compile_context)
/opt/ttforge-toolchain/venv/lib/python3.10/site-packages/forge/compile.py:293: in forge_compile_from_context
    next_stage = stage_to_func[current_stage](context)
/opt/ttforge-toolchain/venv/lib/python3.10/site-packages/forge/compile.py:671: in generate_initial_graph
    module, module_inputs = convert_to_forge_module(
/opt/ttforge-toolchain/venv/lib/python3.10/site-packages/forge/compile.py:1032: in convert_to_forge_module
    forge_module, dev_types, module_inputs = generate_forge_module(
/opt/ttforge-toolchain/venv/lib/python3.10/site-packages/forge/tvm_to_python.py:2062: in generate_forge_module
    module_writers, flattened_inputs = compile_tvm_to_python(
/opt/ttforge-toolchain/venv/lib/python3.10/site-packages/forge/tvm_to_python.py:2149: in compile_tvm_to_python
    from forge.tvm_calls.forge_compile import load_tvm_graph
/opt/ttforge-toolchain/venv/lib/python3.10/site-packages/forge/tvm_calls/forge_compile.py:36: in <module>
    from forge.tvm_calls.relay.op.forge import verify_tvm_compile, flatten_IO, compile_for_forge, partition_for_forge
_ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ 

    # SPDX-FileCopyrightText:  2024 Tenstorrent AI ULC
    #
    # SPDX-License-Identifier: Apache-2.0
>   from .forge import *
E     File "/opt/ttforge-toolchain/venv/lib/python3.10/site-packages/forge/tvm_calls/relay/op/forge.py", line 19
E       from tvm.relay.dataflow_pattern import *from .reportify import dump_graph
E                                               ^^^^
E   SyntaxError: invalid syntax

/opt/ttforge-toolchain/venv/lib/python3.10/site-packages/forge/tvm_calls/relay/op/__init__.py:4: SyntaxError

Check failure on line 232 in forge/test/mlir/operators/eltwise_binary/test_eltwise_binary.py

See this annotation in the file changed.

@github-actions github-actions / TT-Forge-FE Tests

test_eltwise_binary.test_equal[shape13] 

File "/opt/ttforge-toolchain/venv/lib/python3.10/site-packages/forge/tvm_calls/relay/op/forge.py", line 19
    from tvm.relay.dataflow_pattern import *from .reportify import dump_graph
                                            ^^^^
SyntaxError: invalid syntax
Raw output 
shape = (32, 64, 64)

    @pytest.mark.parametrize(
        "shape",
        [
            (1, 128, 28, 28),
            (1, 64, 28, 28),
            (1, 256, 28, 28),
            (1, 128, 14, 14),
            (1, 128, 56, 56),
            (1, 32, 64, 64),
            (1, 512, 7, 7),
            (1, 32, 32, 32),
            (128, 28, 28),
            (64, 28, 28),
            (256, 28, 28),
            (128, 14, 14),
            (128, 56, 56),
            (32, 64, 64),
            (512, 7, 7),
            (32, 32, 32),
            (128, 28),
            (64, 28),
            (256, 28),
            (128, 14),
            (128, 56),
            (32, 64),
            (512, 7),
            (32, 32),
        ],
    )
    @pytest.mark.push
    def test_equal(shape):
        class Equal(nn.Module):
            def __init__(self):
                super().__init__()
    
            def forward(self, x, y):
                return torch.eq(x, y)
    
        x = torch.rand(shape)
        y = x * 2.0
    
        inputs = [x, y]
    
        framework_model = Equal()
>       compiled_model = forge.compile(framework_model, sample_inputs=inputs)

forge/test/mlir/operators/eltwise_binary/test_eltwise_binary.py:232: 
_ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ 
/opt/ttforge-toolchain/venv/lib/python3.10/site-packages/forge/compile.py:251: in compile_main
    return forge_compile_from_context(compile_context)
/opt/ttforge-toolchain/venv/lib/python3.10/site-packages/forge/compile.py:293: in forge_compile_from_context
    next_stage = stage_to_func[current_stage](context)
/opt/ttforge-toolchain/venv/lib/python3.10/site-packages/forge/compile.py:671: in generate_initial_graph
    module, module_inputs = convert_to_forge_module(
/opt/ttforge-toolchain/venv/lib/python3.10/site-packages/forge/compile.py:1032: in convert_to_forge_module
    forge_module, dev_types, module_inputs = generate_forge_module(
/opt/ttforge-toolchain/venv/lib/python3.10/site-packages/forge/tvm_to_python.py:2062: in generate_forge_module
    module_writers, flattened_inputs = compile_tvm_to_python(
/opt/ttforge-toolchain/venv/lib/python3.10/site-packages/forge/tvm_to_python.py:2149: in compile_tvm_to_python
    from forge.tvm_calls.forge_compile import load_tvm_graph
/opt/ttforge-toolchain/venv/lib/python3.10/site-packages/forge/tvm_calls/forge_compile.py:36: in <module>
    from forge.tvm_calls.relay.op.forge import verify_tvm_compile, flatten_IO, compile_for_forge, partition_for_forge
_ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ 

    # SPDX-FileCopyrightText:  2024 Tenstorrent AI ULC
    #
    # SPDX-License-Identifier: Apache-2.0
>   from .forge import *
E     File "/opt/ttforge-toolchain/venv/lib/python3.10/site-packages/forge/tvm_calls/relay/op/forge.py", line 19
E       from tvm.relay.dataflow_pattern import *from .reportify import dump_graph
E                                               ^^^^
E   SyntaxError: invalid syntax

/opt/ttforge-toolchain/venv/lib/python3.10/site-packages/forge/tvm_calls/relay/op/__init__.py:4: SyntaxError

Check failure on line 232 in forge/test/mlir/operators/eltwise_binary/test_eltwise_binary.py

See this annotation in the file changed.

@github-actions github-actions / TT-Forge-FE Tests

test_eltwise_binary.test_equal[shape15] 

File "/opt/ttforge-toolchain/venv/lib/python3.10/site-packages/forge/tvm_calls/relay/op/forge.py", line 19
    from tvm.relay.dataflow_pattern import *from .reportify import dump_graph
                                            ^^^^
SyntaxError: invalid syntax
Raw output 
shape = (32, 32, 32)

    @pytest.mark.parametrize(
        "shape",
        [
            (1, 128, 28, 28),
            (1, 64, 28, 28),
            (1, 256, 28, 28),
            (1, 128, 14, 14),
            (1, 128, 56, 56),
            (1, 32, 64, 64),
            (1, 512, 7, 7),
            (1, 32, 32, 32),
            (128, 28, 28),
            (64, 28, 28),
            (256, 28, 28),
            (128, 14, 14),
            (128, 56, 56),
            (32, 64, 64),
            (512, 7, 7),
            (32, 32, 32),
            (128, 28),
            (64, 28),
            (256, 28),
            (128, 14),
            (128, 56),
            (32, 64),
            (512, 7),
            (32, 32),
        ],
    )
    @pytest.mark.push
    def test_equal(shape):
        class Equal(nn.Module):
            def __init__(self):
                super().__init__()
    
            def forward(self, x, y):
                return torch.eq(x, y)
    
        x = torch.rand(shape)
        y = x * 2.0
    
        inputs = [x, y]
    
        framework_model = Equal()
>       compiled_model = forge.compile(framework_model, sample_inputs=inputs)

forge/test/mlir/operators/eltwise_binary/test_eltwise_binary.py:232: 
_ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ 
/opt/ttforge-toolchain/venv/lib/python3.10/site-packages/forge/compile.py:251: in compile_main
    return forge_compile_from_context(compile_context)
/opt/ttforge-toolchain/venv/lib/python3.10/site-packages/forge/compile.py:293: in forge_compile_from_context
    next_stage = stage_to_func[current_stage](context)
/opt/ttforge-toolchain/venv/lib/python3.10/site-packages/forge/compile.py:671: in generate_initial_graph
    module, module_inputs = convert_to_forge_module(
/opt/ttforge-toolchain/venv/lib/python3.10/site-packages/forge/compile.py:1032: in convert_to_forge_module
    forge_module, dev_types, module_inputs = generate_forge_module(
/opt/ttforge-toolchain/venv/lib/python3.10/site-packages/forge/tvm_to_python.py:2062: in generate_forge_module
    module_writers, flattened_inputs = compile_tvm_to_python(
/opt/ttforge-toolchain/venv/lib/python3.10/site-packages/forge/tvm_to_python.py:2149: in compile_tvm_to_python
    from forge.tvm_calls.forge_compile import load_tvm_graph
/opt/ttforge-toolchain/venv/lib/python3.10/site-packages/forge/tvm_calls/forge_compile.py:36: in <module>
    from forge.tvm_calls.relay.op.forge import verify_tvm_compile, flatten_IO, compile_for_forge, partition_for_forge
_ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ 

    # SPDX-FileCopyrightText:  2024 Tenstorrent AI ULC
    #
    # SPDX-License-Identifier: Apache-2.0
>   from .forge import *
E     File "/opt/ttforge-toolchain/venv/lib/python3.10/site-packages/forge/tvm_calls/relay/op/forge.py", line 19
E       from tvm.relay.dataflow_pattern import *from .reportify import dump_graph
E                                               ^^^^
E   SyntaxError: invalid syntax

/opt/ttforge-toolchain/venv/lib/python3.10/site-packages/forge/tvm_calls/relay/op/__init__.py:4: SyntaxError

Check failure on line 232 in forge/test/mlir/operators/eltwise_binary/test_eltwise_binary.py

See this annotation in the file changed.

@github-actions github-actions / TT-Forge-FE Tests

test_eltwise_binary.test_equal[shape17] 

File "/opt/ttforge-toolchain/venv/lib/python3.10/site-packages/forge/tvm_calls/relay/op/forge.py", line 19
    from tvm.relay.dataflow_pattern import *from .reportify import dump_graph
                                            ^^^^
SyntaxError: invalid syntax
Raw output 
shape = (64, 28)

    @pytest.mark.parametrize(
        "shape",
        [
            (1, 128, 28, 28),
            (1, 64, 28, 28),
            (1, 256, 28, 28),
            (1, 128, 14, 14),
            (1, 128, 56, 56),
            (1, 32, 64, 64),
            (1, 512, 7, 7),
            (1, 32, 32, 32),
            (128, 28, 28),
            (64, 28, 28),
            (256, 28, 28),
            (128, 14, 14),
            (128, 56, 56),
            (32, 64, 64),
            (512, 7, 7),
            (32, 32, 32),
            (128, 28),
            (64, 28),
            (256, 28),
            (128, 14),
            (128, 56),
            (32, 64),
            (512, 7),
            (32, 32),
        ],
    )
    @pytest.mark.push
    def test_equal(shape):
        class Equal(nn.Module):
            def __init__(self):
                super().__init__()
    
            def forward(self, x, y):
                return torch.eq(x, y)
    
        x = torch.rand(shape)
        y = x * 2.0
    
        inputs = [x, y]
    
        framework_model = Equal()
>       compiled_model = forge.compile(framework_model, sample_inputs=inputs)

forge/test/mlir/operators/eltwise_binary/test_eltwise_binary.py:232: 
_ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ 
/opt/ttforge-toolchain/venv/lib/python3.10/site-packages/forge/compile.py:251: in compile_main
    return forge_compile_from_context(compile_context)
/opt/ttforge-toolchain/venv/lib/python3.10/site-packages/forge/compile.py:293: in forge_compile_from_context
    next_stage = stage_to_func[current_stage](context)
/opt/ttforge-toolchain/venv/lib/python3.10/site-packages/forge/compile.py:671: in generate_initial_graph
    module, module_inputs = convert_to_forge_module(
/opt/ttforge-toolchain/venv/lib/python3.10/site-packages/forge/compile.py:1032: in convert_to_forge_module
    forge_module, dev_types, module_inputs = generate_forge_module(
/opt/ttforge-toolchain/venv/lib/python3.10/site-packages/forge/tvm_to_python.py:2062: in generate_forge_module
    module_writers, flattened_inputs = compile_tvm_to_python(
/opt/ttforge-toolchain/venv/lib/python3.10/site-packages/forge/tvm_to_python.py:2149: in compile_tvm_to_python
    from forge.tvm_calls.forge_compile import load_tvm_graph
/opt/ttforge-toolchain/venv/lib/python3.10/site-packages/forge/tvm_calls/forge_compile.py:36: in <module>
    from forge.tvm_calls.relay.op.forge import verify_tvm_compile, flatten_IO, compile_for_forge, partition_for_forge
_ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ 

    # SPDX-FileCopyrightText:  2024 Tenstorrent AI ULC
    #
    # SPDX-License-Identifier: Apache-2.0
>   from .forge import *
E     File "/opt/ttforge-toolchain/venv/lib/python3.10/site-packages/forge/tvm_calls/relay/op/forge.py", line 19
E       from tvm.relay.dataflow_pattern import *from .reportify import dump_graph
E                                               ^^^^
E   SyntaxError: invalid syntax

/opt/ttforge-toolchain/venv/lib/python3.10/site-packages/forge/tvm_calls/relay/op/__init__.py:4: SyntaxError

Check failure on line 232 in forge/test/mlir/operators/eltwise_binary/test_eltwise_binary.py

See this annotation in the file changed.

@github-actions github-actions / TT-Forge-FE Tests

test_eltwise_binary.test_equal[shape19] 

File "/opt/ttforge-toolchain/venv/lib/python3.10/site-packages/forge/tvm_calls/relay/op/forge.py", line 19
    from tvm.relay.dataflow_pattern import *from .reportify import dump_graph
                                            ^^^^
SyntaxError: invalid syntax
Raw output 
shape = (128, 14)

    @pytest.mark.parametrize(
        "shape",
        [
            (1, 128, 28, 28),
            (1, 64, 28, 28),
            (1, 256, 28, 28),
            (1, 128, 14, 14),
            (1, 128, 56, 56),
            (1, 32, 64, 64),
            (1, 512, 7, 7),
            (1, 32, 32, 32),
            (128, 28, 28),
            (64, 28, 28),
            (256, 28, 28),
            (128, 14, 14),
            (128, 56, 56),
            (32, 64, 64),
            (512, 7, 7),
            (32, 32, 32),
            (128, 28),
            (64, 28),
            (256, 28),
            (128, 14),
            (128, 56),
            (32, 64),
            (512, 7),
            (32, 32),
        ],
    )
    @pytest.mark.push
    def test_equal(shape):
        class Equal(nn.Module):
            def __init__(self):
                super().__init__()
    
            def forward(self, x, y):
                return torch.eq(x, y)
    
        x = torch.rand(shape)
        y = x * 2.0
    
        inputs = [x, y]
    
        framework_model = Equal()
>       compiled_model = forge.compile(framework_model, sample_inputs=inputs)

forge/test/mlir/operators/eltwise_binary/test_eltwise_binary.py:232: 
_ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ 
/opt/ttforge-toolchain/venv/lib/python3.10/site-packages/forge/compile.py:251: in compile_main
    return forge_compile_from_context(compile_context)
/opt/ttforge-toolchain/venv/lib/python3.10/site-packages/forge/compile.py:293: in forge_compile_from_context
    next_stage = stage_to_func[current_stage](context)
/opt/ttforge-toolchain/venv/lib/python3.10/site-packages/forge/compile.py:671: in generate_initial_graph
    module, module_inputs = convert_to_forge_module(
/opt/ttforge-toolchain/venv/lib/python3.10/site-packages/forge/compile.py:1032: in convert_to_forge_module
    forge_module, dev_types, module_inputs = generate_forge_module(
/opt/ttforge-toolchain/venv/lib/python3.10/site-packages/forge/tvm_to_python.py:2062: in generate_forge_module
    module_writers, flattened_inputs = compile_tvm_to_python(
/opt/ttforge-toolchain/venv/lib/python3.10/site-packages/forge/tvm_to_python.py:2149: in compile_tvm_to_python
    from forge.tvm_calls.forge_compile import load_tvm_graph
/opt/ttforge-toolchain/venv/lib/python3.10/site-packages/forge/tvm_calls/forge_compile.py:36: in <module>
    from forge.tvm_calls.relay.op.forge import verify_tvm_compile, flatten_IO, compile_for_forge, partition_for_forge
_ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ 

    # SPDX-FileCopyrightText:  2024 Tenstorrent AI ULC
    #
    # SPDX-License-Identifier: Apache-2.0
>   from .forge import *
E     File "/opt/ttforge-toolchain/venv/lib/python3.10/site-packages/forge/tvm_calls/relay/op/forge.py", line 19
E       from tvm.relay.dataflow_pattern import *from .reportify import dump_graph
E                                               ^^^^
E   SyntaxError: invalid syntax

/opt/ttforge-toolchain/venv/lib/python3.10/site-packages/forge/tvm_calls/relay/op/__init__.py:4: SyntaxError

Check failure on line 232 in forge/test/mlir/operators/eltwise_binary/test_eltwise_binary.py

See this annotation in the file changed.

@github-actions github-actions / TT-Forge-FE Tests

test_eltwise_binary.test_equal[shape20] 

File "/opt/ttforge-toolchain/venv/lib/python3.10/site-packages/forge/tvm_calls/relay/op/forge.py", line 19
    from tvm.relay.dataflow_pattern import *from .reportify import dump_graph
                                            ^^^^
SyntaxError: invalid syntax
Raw output 
shape = (128, 56)

    @pytest.mark.parametrize(
        "shape",
        [
            (1, 128, 28, 28),
            (1, 64, 28, 28),
            (1, 256, 28, 28),
            (1, 128, 14, 14),
            (1, 128, 56, 56),
            (1, 32, 64, 64),
            (1, 512, 7, 7),
            (1, 32, 32, 32),
            (128, 28, 28),
            (64, 28, 28),
            (256, 28, 28),
            (128, 14, 14),
            (128, 56, 56),
            (32, 64, 64),
            (512, 7, 7),
            (32, 32, 32),
            (128, 28),
            (64, 28),
            (256, 28),
            (128, 14),
            (128, 56),
            (32, 64),
            (512, 7),
            (32, 32),
        ],
    )
    @pytest.mark.push
    def test_equal(shape):
        class Equal(nn.Module):
            def __init__(self):
                super().__init__()
    
            def forward(self, x, y):
                return torch.eq(x, y)
    
        x = torch.rand(shape)
        y = x * 2.0
    
        inputs = [x, y]
    
        framework_model = Equal()
>       compiled_model = forge.compile(framework_model, sample_inputs=inputs)

forge/test/mlir/operators/eltwise_binary/test_eltwise_binary.py:232: 
_ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ 
/opt/ttforge-toolchain/venv/lib/python3.10/site-packages/forge/compile.py:251: in compile_main
    return forge_compile_from_context(compile_context)
/opt/ttforge-toolchain/venv/lib/python3.10/site-packages/forge/compile.py:293: in forge_compile_from_context
    next_stage = stage_to_func[current_stage](context)
/opt/ttforge-toolchain/venv/lib/python3.10/site-packages/forge/compile.py:671: in generate_initial_graph
    module, module_inputs = convert_to_forge_module(
/opt/ttforge-toolchain/venv/lib/python3.10/site-packages/forge/compile.py:1032: in convert_to_forge_module
    forge_module, dev_types, module_inputs = generate_forge_module(
/opt/ttforge-toolchain/venv/lib/python3.10/site-packages/forge/tvm_to_python.py:2062: in generate_forge_module
    module_writers, flattened_inputs = compile_tvm_to_python(
/opt/ttforge-toolchain/venv/lib/python3.10/site-packages/forge/tvm_to_python.py:2149: in compile_tvm_to_python
    from forge.tvm_calls.forge_compile import load_tvm_graph
/opt/ttforge-toolchain/venv/lib/python3.10/site-packages/forge/tvm_calls/forge_compile.py:36: in <module>
    from forge.tvm_calls.relay.op.forge import verify_tvm_compile, flatten_IO, compile_for_forge, partition_for_forge
_ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ 

    # SPDX-FileCopyrightText:  2024 Tenstorrent AI ULC
    #
    # SPDX-License-Identifier: Apache-2.0
>   from .forge import *
E     File "/opt/ttforge-toolchain/venv/lib/python3.10/site-packages/forge/tvm_calls/relay/op/forge.py", line 19
E       from tvm.relay.dataflow_pattern import *from .reportify import dump_graph
E                                               ^^^^
E   SyntaxError: invalid syntax

/opt/ttforge-toolchain/venv/lib/python3.10/site-packages/forge/tvm_calls/relay/op/__init__.py:4: SyntaxError

Check failure on line 232 in forge/test/mlir/operators/eltwise_binary/test_eltwise_binary.py

See this annotation in the file changed.

@github-actions github-actions / TT-Forge-FE Tests

test_eltwise_binary.test_equal[shape22] 

File "/opt/ttforge-toolchain/venv/lib/python3.10/site-packages/forge/tvm_calls/relay/op/forge.py", line 19
    from tvm.relay.dataflow_pattern import *from .reportify import dump_graph
                                            ^^^^
SyntaxError: invalid syntax
Raw output 
shape = (512, 7)

    @pytest.mark.parametrize(
        "shape",
        [
            (1, 128, 28, 28),
            (1, 64, 28, 28),
            (1, 256, 28, 28),
            (1, 128, 14, 14),
            (1, 128, 56, 56),
            (1, 32, 64, 64),
            (1, 512, 7, 7),
            (1, 32, 32, 32),
            (128, 28, 28),
            (64, 28, 28),
            (256, 28, 28),
            (128, 14, 14),
            (128, 56, 56),
            (32, 64, 64),
            (512, 7, 7),
            (32, 32, 32),
            (128, 28),
            (64, 28),
            (256, 28),
            (128, 14),
            (128, 56),
            (32, 64),
            (512, 7),
            (32, 32),
        ],
    )
    @pytest.mark.push
    def test_equal(shape):
        class Equal(nn.Module):
            def __init__(self):
                super().__init__()
    
            def forward(self, x, y):
                return torch.eq(x, y)
    
        x = torch.rand(shape)
        y = x * 2.0
    
        inputs = [x, y]
    
        framework_model = Equal()
>       compiled_model = forge.compile(framework_model, sample_inputs=inputs)

forge/test/mlir/operators/eltwise_binary/test_eltwise_binary.py:232: 
_ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ 
/opt/ttforge-toolchain/venv/lib/python3.10/site-packages/forge/compile.py:251: in compile_main
    return forge_compile_from_context(compile_context)
/opt/ttforge-toolchain/venv/lib/python3.10/site-packages/forge/compile.py:293: in forge_compile_from_context
    next_stage = stage_to_func[current_stage](context)
/opt/ttforge-toolchain/venv/lib/python3.10/site-packages/forge/compile.py:671: in generate_initial_graph
    module, module_inputs = convert_to_forge_module(
/opt/ttforge-toolchain/venv/lib/python3.10/site-packages/forge/compile.py:1032: in convert_to_forge_module
    forge_module, dev_types, module_inputs = generate_forge_module(
/opt/ttforge-toolchain/venv/lib/python3.10/site-packages/forge/tvm_to_python.py:2062: in generate_forge_module
    module_writers, flattened_inputs = compile_tvm_to_python(
/opt/ttforge-toolchain/venv/lib/python3.10/site-packages/forge/tvm_to_python.py:2149: in compile_tvm_to_python
    from forge.tvm_calls.forge_compile import load_tvm_graph
/opt/ttforge-toolchain/venv/lib/python3.10/site-packages/forge/tvm_calls/forge_compile.py:36: in <module>
    from forge.tvm_calls.relay.op.forge import verify_tvm_compile, flatten_IO, compile_for_forge, partition_for_forge
_ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ 

    # SPDX-FileCopyrightText:  2024 Tenstorrent AI ULC
    #
    # SPDX-License-Identifier: Apache-2.0
>   from .forge import *
E     File "/opt/ttforge-toolchain/venv/lib/python3.10/site-packages/forge/tvm_calls/relay/op/forge.py", line 19
E       from tvm.relay.dataflow_pattern import *from .reportify import dump_graph
E                                               ^^^^
E   SyntaxError: invalid syntax

/opt/ttforge-toolchain/venv/lib/python3.10/site-packages/forge/tvm_calls/relay/op/__init__.py:4: SyntaxError

Check failure on line 249 in forge/test/mlir/operators/eltwise_binary/test_eltwise_binary.py

See this annotation in the file changed.

@github-actions github-actions / TT-Forge-FE Tests

test_eltwise_binary.test_add 

File "/opt/ttforge-toolchain/venv/lib/python3.10/site-packages/forge/tvm_calls/relay/op/forge.py", line 19
    from tvm.relay.dataflow_pattern import *from .reportify import dump_graph
                                            ^^^^
SyntaxError: invalid syntax
Raw output 
@pytest.mark.push
    def test_add():
        class Add(nn.Module):
            def __init__(self):
                super().__init__()
    
            def forward(self, a, b):
                return a + b
    
        inputs = [torch.rand(2, 32, 32), torch.rand(2, 32, 32)]
    
        framework_model = Add()
>       compiled_model = forge.compile(framework_model, sample_inputs=inputs)

forge/test/mlir/operators/eltwise_binary/test_eltwise_binary.py:249: 
_ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ 
/opt/ttforge-toolchain/venv/lib/python3.10/site-packages/forge/compile.py:251: in compile_main
    return forge_compile_from_context(compile_context)
/opt/ttforge-toolchain/venv/lib/python3.10/site-packages/forge/compile.py:293: in forge_compile_from_context
    next_stage = stage_to_func[current_stage](context)
/opt/ttforge-toolchain/venv/lib/python3.10/site-packages/forge/compile.py:671: in generate_initial_graph
    module, module_inputs = convert_to_forge_module(
/opt/ttforge-toolchain/venv/lib/python3.10/site-packages/forge/compile.py:1032: in convert_to_forge_module
    forge_module, dev_types, module_inputs = generate_forge_module(
/opt/ttforge-toolchain/venv/lib/python3.10/site-packages/forge/tvm_to_python.py:2062: in generate_forge_module
    module_writers, flattened_inputs = compile_tvm_to_python(
/opt/ttforge-toolchain/venv/lib/python3.10/site-packages/forge/tvm_to_python.py:2149: in compile_tvm_to_python
    from forge.tvm_calls.forge_compile import load_tvm_graph
/opt/ttforge-toolchain/venv/lib/python3.10/site-packages/forge/tvm_calls/forge_compile.py:36: in <module>
    from forge.tvm_calls.relay.op.forge import verify_tvm_compile, flatten_IO, compile_for_forge, partition_for_forge
_ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ 

    # SPDX-FileCopyrightText:  2024 Tenstorrent AI ULC
    #
    # SPDX-License-Identifier: Apache-2.0
>   from .forge import *
E     File "/opt/ttforge-toolchain/venv/lib/python3.10/site-packages/forge/tvm_calls/relay/op/forge.py", line 19
E       from tvm.relay.dataflow_pattern import *from .reportify import dump_graph
E                                               ^^^^
E   SyntaxError: invalid syntax

/opt/ttforge-toolchain/venv/lib/python3.10/site-packages/forge/tvm_calls/relay/op/__init__.py:4: SyntaxError
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