mirror of
https://github.com/NVIDIA/Model-Optimizer.git
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124 lines
3.9 KiB
Python
124 lines
3.9 KiB
Python
# SPDX-FileCopyrightText: Copyright (c) 2024 NVIDIA CORPORATION & AFFILIATES. All rights reserved.
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# SPDX-License-Identifier: Apache-2.0
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#
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# Licensed under the Apache License, Version 2.0 (the "License");
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# you may not use this file except in compliance with the License.
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# You may obtain a copy of the License at
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#
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# http://www.apache.org/licenses/LICENSE-2.0
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#
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# Unless required by applicable law or agreed to in writing, software
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# distributed under the License is distributed on an "AS IS" BASIS,
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# WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
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# See the License for the specific language governing permissions and
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# limitations under the License.
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"""Quantized convolution."""
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import torch.nn as nn
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from ... import tensor_quant
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from .quant_module import QuantLinearConvBase, QuantModuleRegistry, _LegacyQuantLinearConvBaseMixin
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__all__ = [
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"Conv1d",
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"Conv2d",
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"Conv3d",
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"ConvTranspose1d",
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"ConvTranspose2d",
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"ConvTranspose3d",
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"QuantConv1d",
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"QuantConv2d",
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"QuantConv3d",
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"QuantConvTranspose1d",
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"QuantConvTranspose2d",
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"QuantConvTranspose3d",
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]
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@QuantModuleRegistry.register({nn.Conv1d: "nn.Conv1d"})
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class _QuantConv1d(QuantLinearConvBase):
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"""Quantized 1D convolution."""
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default_quant_desc_weight = tensor_quant.QUANT_DESC_8BIT_CONV1D_WEIGHT_PER_CHANNEL
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class QuantConv1d(_LegacyQuantLinearConvBaseMixin, nn.Conv1d):
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"""Quantized 1D convolution."""
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default_quant_desc_weight = _QuantConv1d.default_quant_desc_weight
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@QuantModuleRegistry.register({nn.Conv2d: "nn.Conv2d"})
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class _QuantConv2d(QuantLinearConvBase):
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"""Quantized 2D convolution."""
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default_quant_desc_weight = tensor_quant.QUANT_DESC_8BIT_CONV2D_WEIGHT_PER_CHANNEL
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class QuantConv2d(_LegacyQuantLinearConvBaseMixin, nn.Conv2d):
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"""Quantized 2D convolution."""
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default_quant_desc_weight = _QuantConv2d.default_quant_desc_weight
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@QuantModuleRegistry.register({nn.Conv3d: "nn.Conv3d"})
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class _QuantConv3d(QuantLinearConvBase):
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"""Quantized 3D convolution."""
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default_quant_desc_weight = tensor_quant.QUANT_DESC_8BIT_CONV3D_WEIGHT_PER_CHANNEL
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class QuantConv3d(_LegacyQuantLinearConvBaseMixin, nn.Conv3d):
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"""Quantized 3D convolution."""
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default_quant_desc_weight = _QuantConv3d.default_quant_desc_weight
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@QuantModuleRegistry.register({nn.ConvTranspose1d: "nn.ConvTranspose1d"})
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class _QuantConvTranspose1d(QuantLinearConvBase):
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"""Quantized 1D transposed convolution."""
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default_quant_desc_weight = tensor_quant.QUANT_DESC_8BIT_CONVTRANSPOSE1D_WEIGHT_PER_CHANNEL
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class QuantConvTranspose1d(_LegacyQuantLinearConvBaseMixin, nn.ConvTranspose1d):
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"""Quantized 1D transposed convolution."""
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default_quant_desc_weight = _QuantConvTranspose1d.default_quant_desc_weight
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@QuantModuleRegistry.register({nn.ConvTranspose2d: "nn.ConvTranspose2d"})
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class _QuantConvTranspose2d(QuantLinearConvBase):
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"""Quantized 2D transposed convolution."""
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default_quant_desc_weight = tensor_quant.QUANT_DESC_8BIT_CONVTRANSPOSE2D_WEIGHT_PER_CHANNEL
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class QuantConvTranspose2d(_LegacyQuantLinearConvBaseMixin, nn.ConvTranspose2d):
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"""Quantized 2D transposed convolution."""
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default_quant_desc_weight = _QuantConvTranspose2d.default_quant_desc_weight
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@QuantModuleRegistry.register({nn.ConvTranspose3d: "nn.ConvTranspose3d"})
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class _QuantConvTranspose3d(QuantLinearConvBase):
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"""Quantized 3D transposed convolution."""
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default_quant_desc_weight = tensor_quant.QUANT_DESC_8BIT_CONVTRANSPOSE3D_WEIGHT_PER_CHANNEL
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class QuantConvTranspose3d(_LegacyQuantLinearConvBaseMixin, nn.ConvTranspose3d):
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"""Quantized 3D transposed convolution."""
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default_quant_desc_weight = _QuantConvTranspose3d.default_quant_desc_weight
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# Define alias with Quant prefix
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Conv1d = QuantConv1d
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Conv2d = QuantConv2d
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Conv3d = QuantConv3d
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ConvTranspose1d = QuantConvTranspose1d
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ConvTranspose2d = QuantConvTranspose2d
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ConvTranspose3d = QuantConvTranspose3d
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