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Add support for complex yolov4 model #1318
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model.eval() | ||
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# prepare sample input | ||
sample_input = torch.randn((1, 3, 608, 608)) |
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Why don't we load any image here? Any reason to go for random inputs?
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Due to the size of the dataset , I am unable to figure out a way to pass single input data. that's why I passed random input for now. will figure out a way and will provide the actual input once the model passes end-to-end.
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can you please raise an issue for the same to address this in future and to make sure we don't miss it?
cc: @nvukobratTT
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@ashokkumarkannan1 @nvukobratTT
Marked the PR as draft due to the presence of bunch of code from github.
sample_input = torch.randn((1, 3, 608, 608)) | ||
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# Forge compile framework model | ||
compiled_model = forge.compile(model, sample_inputs=[sample_input], module_name=module_name) |
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Pls add Verify function
# | ||
# SPDX-License-Identifier: Apache-2.0 | ||
""" | ||
# -*- coding: utf-8 -*- |
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We need to wait for @nvukobratTT's inputs, to place this GitHub copied files in a proper place.
forge/test/models/utils.py
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@@ -36,6 +36,7 @@ class Task(StrEnum): | |||
CONDITIONAL_GENERATION = "cond_gen" | |||
IMAGE_ENCODING = "img_enc" | |||
VISUAL_BACKBONE = "visual_bb" | |||
OBJECT_DETECTION_3D = "object_detection_3D" |
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rename "object_detection_3D" to "object_detection_3d" to follow lowercase.
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