121 lines
5.0 KiB
C
121 lines
5.0 KiB
C
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/* Copyright 2017 The TensorFlow Authors. All Rights Reserved.
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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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http://www.apache.org/licenses/LICENSE-2.0
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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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==============================================================================*/
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#ifndef TENSORFLOW_LITE_KERNELS_PADDING_H_
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#define TENSORFLOW_LITE_KERNELS_PADDING_H_
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#include "tensorflow/lite/c/builtin_op_data.h"
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#include "tensorflow/lite/kernels/internal/types.h"
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namespace tflite {
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inline int ComputePadding(int stride, int dilation_rate, int in_size,
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int filter_size, int out_size)
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{
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int effective_filter_size = (filter_size - 1) * dilation_rate + 1;
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int padding = ((out_size - 1) * stride + effective_filter_size - in_size) / 2;
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return padding > 0 ? padding : 0;
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}
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// It's not guaranteed that padding is symmetric. It's important to keep
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// offset for algorithms need all paddings.
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inline int ComputePaddingWithOffset(int stride, int dilation_rate, int in_size,
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int filter_size, int out_size,
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int *offset)
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{
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int effective_filter_size = (filter_size - 1) * dilation_rate + 1;
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int total_padding =
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((out_size - 1) * stride + effective_filter_size - in_size);
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total_padding = total_padding > 0 ? total_padding : 0;
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*offset = total_padding % 2;
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return total_padding / 2;
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}
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// Matching GetWindowedOutputSize in TensorFlow.
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inline int ComputeOutSize(TfLitePadding padding, int image_size,
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int filter_size, int stride, int dilation_rate = 1)
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{
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int effective_filter_size = (filter_size - 1) * dilation_rate + 1;
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// TODO(b/186448822): This uses 0 since the function has no other way to
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// report error case
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if (stride == 0)
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return 0;
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switch (padding) {
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case kTfLitePaddingSame:
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return (image_size + stride - 1) / stride;
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case kTfLitePaddingValid:
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return (image_size + stride - effective_filter_size) / stride;
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default:
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return 0;
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}
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}
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inline TfLitePaddingValues ComputePaddingHeightWidth(
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int stride_height, int stride_width, int dilation_rate_height,
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int dilation_rate_width, int in_height, int in_width, int filter_height,
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int filter_width, TfLitePadding padding, int *out_height, int *out_width)
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{
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*out_width = ComputeOutSize(padding, in_width, filter_width, stride_width,
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dilation_rate_width);
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*out_height = ComputeOutSize(padding, in_height, filter_height, stride_height,
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dilation_rate_height);
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TfLitePaddingValues padding_values;
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int offset = 0;
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padding_values.height =
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ComputePaddingWithOffset(stride_height, dilation_rate_height, in_height,
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filter_height, *out_height, &offset);
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padding_values.height_offset = offset;
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padding_values.width =
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ComputePaddingWithOffset(stride_width, dilation_rate_width, in_width,
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filter_width, *out_width, &offset);
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padding_values.width_offset = offset;
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return padding_values;
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}
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inline Padding3DValues ComputePadding3DValues(
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int stride_height, int stride_width, int stride_depth,
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int dilation_rate_height, int dilation_rate_width, int dilation_rate_depth,
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int in_height, int in_width, int in_depth, int filter_height,
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int filter_width, int filter_depth, TfLitePadding padding, int *out_height,
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int *out_width, int *out_depth)
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{
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*out_width = ComputeOutSize(padding, in_width, filter_width, stride_width,
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dilation_rate_width);
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*out_height = ComputeOutSize(padding, in_height, filter_height, stride_height,
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dilation_rate_height);
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*out_depth = ComputeOutSize(padding, in_depth, filter_depth, stride_depth,
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dilation_rate_depth);
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Padding3DValues padding_values;
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int offset = 0;
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padding_values.depth =
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ComputePaddingWithOffset(stride_depth, dilation_rate_depth, in_depth,
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filter_depth, *out_depth, &offset);
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padding_values.depth_offset = offset;
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padding_values.height =
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ComputePaddingWithOffset(stride_height, dilation_rate_height, in_height,
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filter_height, *out_height, &offset);
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padding_values.height_offset = offset;
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padding_values.width =
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ComputePaddingWithOffset(stride_width, dilation_rate_width, in_width,
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filter_width, *out_width, &offset);
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padding_values.width_offset = offset;
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return padding_values;
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}
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} // namespace tflite
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#endif // TENSORFLOW_LITE_KERNELS_PADDING_H_
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