#0: remove device from all maxpool calls in models

tenstorrent · Oct 9, 2024 · 82ba7a5 · 82ba7a5
1 parent 07f6e14
commit 82ba7a5
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Showing 10 changed files with 1 addition and 18 deletions.
diff --git a/models/demos/convnet_mnist/tt/convnet_mnist.py b/models/demos/convnet_mnist/tt/convnet_mnist.py
@@ -74,7 +74,6 @@ def convnet_mnist(
             stride=[1, 1],
             padding=[0, 0],
             dilation=[1, 1],
-            device=device,
         )
 
     [x, out_height, out_width, weights_device, bias_device] = ttnn.conv2d(
@@ -118,7 +117,6 @@ def convnet_mnist(
             stride=[1, 1],
             padding=[0, 0],
             dilation=[1, 1],
-            device=device,
         )
     x = ttnn.from_device(x)
     x = ttnn.reshape(x, (x.shape[0], -1))

diff --git a/models/demos/ttnn_resnet/tt/ttnn_functional_resnet50_large_new_conv_api.py b/models/demos/ttnn_resnet/tt/ttnn_functional_resnet50_large_new_conv_api.py
@@ -560,7 +560,6 @@ def first_run(self, input_tensor, device, batch_size, ops_parallel_config) -> tt
             stride=[2, 2],
             padding=[1, 1],
             dilation=[1, 1],
-            device=device,
         )
 
         x_height = 128
@@ -867,7 +866,6 @@ def optimized_run(self, input_tensor, device, batch_size, ops_parallel_config, c
             stride=[2, 2],
             padding=[1, 1],
             dilation=[1, 1],
-            device=device,
         )
 
         x_height = 128

diff --git a/models/demos/ttnn_resnet/tt/ttnn_functional_resnet50_new_conv_api.py b/models/demos/ttnn_resnet/tt/ttnn_functional_resnet50_new_conv_api.py
@@ -746,7 +746,6 @@ def run(self, input_tensor, device, ops_parallel_config, conv_op_cache={}) -> tt
             stride=[2, 2],
             padding=[1, 1],
             dilation=[1, 1],
-            device=device,
         )
 
         x_height = 56

diff --git a/models/demos/ttnn_resnet/tt/ttnn_functional_resnet50_xlarge_new_conv_api.py b/models/demos/ttnn_resnet/tt/ttnn_functional_resnet50_xlarge_new_conv_api.py
@@ -557,7 +557,6 @@ def first_run(self, input_tensor, device, batch_size, ops_parallel_config) -> tt
             stride=[2, 2],
             padding=[1, 1],
             dilation=[1, 1],
-            device=device,
         )
 
         x_height = 224
@@ -861,7 +860,6 @@ def optimized_run(self, input_tensor, device, batch_size, ops_parallel_config, c
             stride=[2, 2],
             padding=[1, 1],
             dilation=[1, 1],
-            device=device,
         )
 
         x_height = 224

diff --git a/models/demos/ttnn_resnet/tt/ttnn_functional_resnet50_xlarge_new_conv_api_24.py b/models/demos/ttnn_resnet/tt/ttnn_functional_resnet50_xlarge_new_conv_api_24.py
@@ -559,7 +559,6 @@ def first_run(self, input_tensor, device, batch_size, ops_parallel_config) -> tt
             stride=[2, 2],
             padding=[1, 1],
             dilation=[1, 1],
-            device=device,
         )
 
         x_height = 224
@@ -891,7 +890,6 @@ def optimized_run(self, input_tensor, device, batch_size, ops_parallel_config, c
             stride=[2, 2],
             padding=[1, 1],
             dilation=[1, 1],
-            device=device,
         )
 
         x_height = 224

diff --git a/models/demos/ttnn_resnet/tt/ttnn_functional_resnet50_xxlarge_new_conv_api.py b/models/demos/ttnn_resnet/tt/ttnn_functional_resnet50_xxlarge_new_conv_api.py
@@ -631,7 +631,6 @@ def first_run(self, input_tensor, device, batch_size, ops_parallel_config) -> tt
             stride=[2, 2],
             padding=[1, 1],
             dilation=[1, 1],
-            device=device,
         )
 
         x_height = 256
@@ -965,7 +964,6 @@ def optimized_run(self, input_tensor, device, batch_size, ops_parallel_config, c
             stride=[2, 2],
             padding=[1, 1],
             dilation=[1, 1],
-            device=device,
         )
 
         x_height = 256

diff --git a/models/demos/vgg/tt/ttnn_vgg.py b/models/demos/vgg/tt/ttnn_vgg.py
@@ -78,7 +78,6 @@ def ttnn_vgg16(
                 stride=[2, 2],
                 padding=[0, 0],
                 dilation=[1, 1],
-                device=device,
             )
             ttnn.deallocate(ttact_d)
             tt_x = ttnn.from_device(tt_x)
@@ -206,7 +205,7 @@ def ttnn_vgg11(
                 stride=[2, 2],
                 padding=[0, 0],
                 dilation=[1, 1],
-                device=device,
+                devie=device,
             )
             tt_x = ttnn.from_device(tt_x)
             ttnn.deallocate(ttact_d)

diff --git a/models/experimental/functional_unet/tt/unet_shallow_ttnn.py b/models/experimental/functional_unet/tt/unet_shallow_ttnn.py
@@ -232,7 +232,6 @@ def __call__(self, x):
             stride=[self.pool.stride, self.pool.stride],
             padding=[self.pool.padding, self.pool.padding],
             dilation=[self.pool.dilation, self.pool.dilation],
-            device=self.device,
         )
         return x
 

diff --git a/models/experimental/yolov4/ttnn/neck.py b/models/experimental/yolov4/ttnn/neck.py
@@ -191,7 +191,6 @@ def __call__(self, device, input_tensor):
             stride=[1, 1],
             padding=[2, 2],
             dilation=[1, 1],
-            device=device,
         )
         pool_2 = ttnn.max_pool2d(
             input_tensor=output_tensor,
@@ -203,7 +202,6 @@ def __call__(self, device, input_tensor):
             stride=[1, 1],
             padding=[4, 4],
             dilation=[1, 1],
-            device=device,
         )
         pool_3 = ttnn.max_pool2d(
             input_tensor=output_tensor,
@@ -215,7 +213,6 @@ def __call__(self, device, input_tensor):
             stride=[1, 1],
             padding=[6, 6],
             dilation=[1, 1],
-            device=device,
         )
 
         pool_1 = ttnn.sharded_to_interleaved(pool_1, ttnn.L1_MEMORY_CONFIG)

diff --git a/tests/ttnn/sweep_tests/sweeps/sweeps/max_pool2d.py b/tests/ttnn/sweep_tests/sweeps/sweeps/max_pool2d.py
@@ -95,7 +95,6 @@ def run(
         stride=[stride_h, stride_w],
         padding=[pad_h, pad_w],
         dilation=[dilation_h, dilation_w],
-        device=device,
     )
     out_padded = out_d.cpu()
     out_pytorch_padded = ttnn.to_torch(out_padded)