/external/tensorflow/tensorflow/core/kernels/ |
D | mkl_conv_ops.h | 76 int stride_rows = GetTensorDim(strides_, data_format_, 'H'); in GetStridesInMklOrder() 77 int stride_cols = GetTensorDim(strides_, data_format_, 'W'); in GetStridesInMklOrder() 80 int stride_planes = GetTensorDim(strides_, data_format_, '0'); in GetStridesInMklOrder() 81 int stride_rows = GetTensorDim(strides_, data_format_, '1'); in GetStridesInMklOrder() 82 int stride_cols = GetTensorDim(strides_, data_format_, '2'); in GetStridesInMklOrder() 93 int dilations_rows = GetTensorDim(dilations_, data_format_, 'H'); in GetDilationsInMklOrder() 94 int dilations_cols = GetTensorDim(dilations_, data_format_, 'W'); in GetDilationsInMklOrder() 97 int dilations_planes = GetTensorDim(dilations_, data_format_, '0'); in GetDilationsInMklOrder() 98 int dilations_rows = GetTensorDim(dilations_, data_format_, '1'); in GetDilationsInMklOrder() 99 int dilations_cols = GetTensorDim(dilations_, data_format_, '2'); in GetDilationsInMklOrder() [all …]
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D | pooling_ops_3d.cc | 63 depth = GetTensorDim(tensor_in_shape, data_format, 'C'); in Pool3dParameters() 64 tensor_in_planes = GetTensorDim(tensor_in_shape, data_format, '0'); in Pool3dParameters() 65 tensor_in_rows = GetTensorDim(tensor_in_shape, data_format, '1'); in Pool3dParameters() 66 tensor_in_cols = GetTensorDim(tensor_in_shape, data_format, '2'); in Pool3dParameters() 67 tensor_in_batch = GetTensorDim(tensor_in_shape, data_format, 'N'); in Pool3dParameters() 68 window_planes = GetTensorDim(ksize, data_format, '0'); in Pool3dParameters() 69 window_rows = GetTensorDim(ksize, data_format, '1'); in Pool3dParameters() 70 window_cols = GetTensorDim(ksize, data_format, '2'); in Pool3dParameters() 71 depth_window = GetTensorDim(ksize, data_format, 'C'); in Pool3dParameters() 72 plane_stride = GetTensorDim(stride, data_format, '0'); in Pool3dParameters() [all …]
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D | conv_ops_3d.cc | 87 (GetTensorDim(stride_, data_format_, 'N') == 1 && in Conv3DOp() 88 GetTensorDim(stride_, data_format_, 'C') == 1), in Conv3DOp() 93 (GetTensorDim(stride_, data_format_, '0') > 0 && in Conv3DOp() 94 GetTensorDim(stride_, data_format_, '1') > 0 && in Conv3DOp() 95 GetTensorDim(stride_, data_format_, '2') > 0), in Conv3DOp() 102 (GetTensorDim(dilation_, data_format_, 'N') == 1 && in Conv3DOp() 103 GetTensorDim(dilation_, data_format_, 'C') == 1), in Conv3DOp() 109 (GetTensorDim(dilation_, data_format_, '0') > 0 && in Conv3DOp() 110 GetTensorDim(dilation_, data_format_, '1') > 0 && in Conv3DOp() 111 GetTensorDim(dilation_, data_format_, '2') > 0), in Conv3DOp() [all …]
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D | mkl_pooling_ops_common.cc | 234 depth = GetTensorDim(tensor_in_shape, data_format, 'C'); in Init() 237 tensor_in_cols = GetTensorDim(tensor_in_shape, data_format, 'W'); in Init() 238 tensor_in_rows = GetTensorDim(tensor_in_shape, data_format, 'H'); in Init() 241 tensor_in_planes = GetTensorDim(tensor_in_shape, data_format, '0'); in Init() 242 tensor_in_rows = GetTensorDim(tensor_in_shape, data_format, '1'); in Init() 243 tensor_in_cols = GetTensorDim(tensor_in_shape, data_format, '2'); in Init() 245 tensor_in_batch = GetTensorDim(tensor_in_shape, data_format, 'N'); in Init() 303 window_rows = GetTensorDim(ksize, data_format, 'H'); in Init() 304 window_cols = GetTensorDim(ksize, data_format, 'W'); in Init() 305 depth_window = GetTensorDim(ksize, data_format, 'C'); in Init() [all …]
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D | conv_grad_ops_3d.cc | 188 (GetTensorDim(dilation_, data_format_, 'C') == 1 && in Conv3DBackpropInputOp() 189 GetTensorDim(dilation_, data_format_, 'N') == 1), in Conv3DBackpropInputOp() 196 (GetTensorDim(dilation_, data_format_, '0') == 1 && in Conv3DBackpropInputOp() 197 GetTensorDim(dilation_, data_format_, '1') == 1 && in Conv3DBackpropInputOp() 198 GetTensorDim(dilation_, data_format_, '2') == 1), in Conv3DBackpropInputOp() 209 (GetTensorDim(stride_, data_format_, 'C') == 1 && in Conv3DBackpropInputOp() 210 GetTensorDim(stride_, data_format_, 'N') == 1), in Conv3DBackpropInputOp() 294 (GetTensorDim(dilation_, data_format_, 'C') == 1 && in Conv3DCustomBackpropInputOp() 295 GetTensorDim(dilation_, data_format_, 'N') == 1), in Conv3DCustomBackpropInputOp() 302 (GetTensorDim(dilation_, data_format_, '0') == 1 && in Conv3DCustomBackpropInputOp() [all …]
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D | pooling_ops_3d_sycl.h | 186 const int out_planes = GetTensorDim(*output, data_format, '0'); 187 const int out_rows = GetTensorDim(*output, data_format, '1'); 188 const int out_cols = GetTensorDim(*output, data_format, '2'); 189 const int batch = GetTensorDim(tensor_in, data_format, 'N'); 190 const int in_planes = GetTensorDim(tensor_in, data_format, '0'); 191 const int in_rows = GetTensorDim(tensor_in, data_format, '1'); 192 const int in_cols = GetTensorDim(tensor_in, data_format, '2'); 193 const int depth = GetTensorDim(tensor_in, data_format, 'C'); 355 const int batch = GetTensorDim(tensor_in, data_format, 'N'); 356 const int in_planes = GetTensorDim(tensor_in, data_format, '0'); [all …]
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D | conv_ops.cc | 141 const int64 in_depth = GetTensorDim(input, data_format, 'C'); in operator ()() 304 const int64 stride_n = GetTensorDim(strides, data_format, 'N'); in InitConv2DParameters() 305 const int64 stride_c = GetTensorDim(strides, data_format, 'C'); in InitConv2DParameters() 306 const int64 stride_h = GetTensorDim(strides, data_format, 'H'); in InitConv2DParameters() 307 const int64 stride_w = GetTensorDim(strides, data_format, 'W'); in InitConv2DParameters() 316 const int64 dilation_n = GetTensorDim(dilations, data_format, 'N'); in InitConv2DParameters() 317 const int64 dilation_c = GetTensorDim(dilations, data_format, 'C'); in InitConv2DParameters() 318 const int64 dilation_h = GetTensorDim(dilations, data_format, 'H'); in InitConv2DParameters() 319 const int64 dilation_w = GetTensorDim(dilations, data_format, 'W'); in InitConv2DParameters() 353 const int64 in_depth_raw = GetTensorDim(input, params.data_format, 'C'); in ComputeConv2DDimension() [all …]
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D | pooling_ops_common.cc | 61 depth = GetTensorDim(tensor_in_shape, data_format, 'C') * in PoolParameters() 63 tensor_in_cols = GetTensorDim(tensor_in_shape, data_format, 'W'); in PoolParameters() 64 tensor_in_rows = GetTensorDim(tensor_in_shape, data_format, 'H'); in PoolParameters() 65 tensor_in_batch = GetTensorDim(tensor_in_shape, data_format, 'N'); in PoolParameters() 66 window_rows = GetTensorDim(ksize, data_format, 'H'); in PoolParameters() 67 window_cols = GetTensorDim(ksize, data_format, 'W'); in PoolParameters() 68 depth_window = GetTensorDim(ksize, data_format, 'C'); in PoolParameters() 69 row_stride = GetTensorDim(stride, data_format, 'H'); in PoolParameters() 70 col_stride = GetTensorDim(stride, data_format, 'W'); in PoolParameters() 71 depth_stride = GetTensorDim(stride, data_format, 'C'); in PoolParameters()
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D | cudnn_pooling_gpu.cc | 44 const int64 in_batch = GetTensorDim(tensor_in, data_format, 'N'); in Compute() 45 const int64 in_features = GetTensorDim(tensor_in, data_format, 'C'); in Compute() 87 GetTensorDim(tensor_in, data_format, '2' - i)); in Compute() 89 GetTensorDim(out_shape, data_format, '2' - i)); in Compute() 130 const int64 in_batch = GetTensorDim(tensor_in_shape, data_format, 'N'); in Compute() 131 const int64 in_features = GetTensorDim(tensor_in_shape, data_format, 'C'); in Compute() 208 dim_i, GetTensorDim(tensor_in_shape, data_format, '2' - i)); in Compute()
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D | conv_grad_input_ops.cc | 590 int stride_n = GetTensorDim(strides_, data_format_, 'N'); in Conv2DSlowBackpropInputOp() 591 int stride_c = GetTensorDim(strides_, data_format_, 'C'); in Conv2DSlowBackpropInputOp() 592 int stride_h = GetTensorDim(strides_, data_format_, 'H'); in Conv2DSlowBackpropInputOp() 593 int stride_w = GetTensorDim(strides_, data_format_, 'W'); in Conv2DSlowBackpropInputOp() 605 int dilation_n = GetTensorDim(dilations_, data_format_, 'N'); in Conv2DSlowBackpropInputOp() 606 int dilation_c = GetTensorDim(dilations_, data_format_, 'C'); in Conv2DSlowBackpropInputOp() 607 int dilation_h = GetTensorDim(dilations_, data_format_, 'H'); in Conv2DSlowBackpropInputOp() 608 int dilation_w = GetTensorDim(dilations_, data_format_, 'W'); in Conv2DSlowBackpropInputOp() 656 const int stride_rows = GetTensorDim(strides_, data_format_, 'H'); in Compute() 657 const int stride_cols = GetTensorDim(strides_, data_format_, 'W'); in Compute() [all …]
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D | conv_grad_filter_ops.cc | 453 int stride_n = GetTensorDim(strides_, data_format_, 'N'); in Conv2DSlowBackpropFilterOp() 454 int stride_c = GetTensorDim(strides_, data_format_, 'C'); in Conv2DSlowBackpropFilterOp() 455 int stride_h = GetTensorDim(strides_, data_format_, 'H'); in Conv2DSlowBackpropFilterOp() 456 int stride_w = GetTensorDim(strides_, data_format_, 'W'); in Conv2DSlowBackpropFilterOp() 468 int dilation_n = GetTensorDim(dilations_, data_format_, 'N'); in Conv2DSlowBackpropFilterOp() 469 int dilation_c = GetTensorDim(dilations_, data_format_, 'C'); in Conv2DSlowBackpropFilterOp() 470 int dilation_h = GetTensorDim(dilations_, data_format_, 'H'); in Conv2DSlowBackpropFilterOp() 471 int dilation_w = GetTensorDim(dilations_, data_format_, 'W'); in Conv2DSlowBackpropFilterOp() 519 const int stride_rows = GetTensorDim(strides_, data_format_, 'H'); in Compute() 520 const int stride_cols = GetTensorDim(strides_, data_format_, 'W'); in Compute() [all …]
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D | conv_ops_using_gemm.cc | 444 const int64 stride_n = GetTensorDim(strides_, data_format_, 'N'); in Conv2DUsingGemmOp() 445 const int64 stride_c = GetTensorDim(strides_, data_format_, 'C'); in Conv2DUsingGemmOp() 479 const int64 in_depth = GetTensorDim(input, data_format_, 'C'); in Compute() 490 const int64 input_rows_raw = GetTensorDim(input, data_format_, 'H'); in Compute() 500 const int64 input_cols_raw = GetTensorDim(input, data_format_, 'W'); in Compute() 509 const int64 batch_raw = GetTensorDim(input, data_format_, 'N'); in Compute() 517 const int stride_rows = GetTensorDim(strides_, data_format_, 'H'); in Compute() 518 const int stride_cols = GetTensorDim(strides_, data_format_, 'W'); in Compute()
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D | mkl_conv_grad_bias_ops.cc | 83 mkl_context.c_size = GetTensorDim(input, data_format_, 'C'); in Compute() 109 mkl_context.in_sizes[MklDims::W] = GetTensorDim(input, data_format_, 'W'); in Compute() 110 mkl_context.in_sizes[MklDims::H] = GetTensorDim(input, data_format_, 'H'); in Compute() 111 mkl_context.in_sizes[MklDims::C] = GetTensorDim(input, data_format_, 'C'); in Compute() 112 mkl_context.in_sizes[MklDims::N] = GetTensorDim(input, data_format_, 'N'); in Compute()
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D | depthwise_conv_op.cc | 277 stride_ = GetTensorDim(strides_, data_format_, 'H'); in DepthwiseConv2dNativeOp() 278 const int64 stride_w = GetTensorDim(strides_, data_format_, 'W'); in DepthwiseConv2dNativeOp() 279 const int64 stride_n = GetTensorDim(strides_, data_format_, 'N'); in DepthwiseConv2dNativeOp() 280 const int64 stride_c = GetTensorDim(strides_, data_format_, 'C'); in DepthwiseConv2dNativeOp() 317 const int64 in_depth = GetTensorDim(input, data_format_, 'C'); in Compute() 329 const int64 input_rows_raw = GetTensorDim(input, data_format_, 'H'); in Compute() 337 const int64 input_cols_raw = GetTensorDim(input, data_format_, 'W'); in Compute()
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D | depthwise_conv_grad_op.cc | 70 const int64 input_rows_raw = GetTensorDim(input_shape, data_format_, 'H'); \ 76 const int64 input_cols_raw = GetTensorDim(input_shape, data_format_, 'W'); \ 85 GetTensorDim(out_backprop.shape(), data_format_, 'H'); \ 92 GetTensorDim(out_backprop.shape(), data_format_, 'W'); \ 98 const int64 in_depth = GetTensorDim(input_shape, data_format_, 'C'); \ 104 GetTensorDim(out_backprop.shape(), data_format_, 'C'); \ 551 stride_ = GetTensorDim(strides_, data_format_, 'H'); in DepthwiseConv2dNativeBackpropInputOp() 552 const int64 stride_w = GetTensorDim(strides_, data_format_, 'W'); in DepthwiseConv2dNativeBackpropInputOp() 553 const int64 stride_n = GetTensorDim(strides_, data_format_, 'N'); in DepthwiseConv2dNativeBackpropInputOp() 554 const int64 stride_c = GetTensorDim(strides_, data_format_, 'C'); in DepthwiseConv2dNativeBackpropInputOp() [all …]
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D | maxpooling_op.cc | 365 const int32 ksize_n = GetTensorDim(ksize_, data_format_, 'N'); in MaxPoolingGradOp() 366 const int32 stride_n = GetTensorDim(stride_, data_format_, 'N'); in MaxPoolingGradOp() 413 const int32 ksize_n = GetTensorDim(ksize, data_format_, 'N'); in Compute() 414 const int32 stride_n = GetTensorDim(stride, data_format_, 'N'); in Compute() 672 const int32 ksize_n = GetTensorDim(ksize_, data_format_, 'N'); in MaxPoolingGradGradOp() 673 const int32 stride_n = GetTensorDim(stride_, data_format_, 'N'); in MaxPoolingGradGradOp() 720 const int32 ksize_n = GetTensorDim(ksize, data_format_, 'N'); in Compute() 721 const int32 stride_n = GetTensorDim(stride, data_format_, 'N'); in Compute() 967 GetTensorDim(grad_out->shape(), FORMAT_NHWC, 'N'); in launch() 998 const int64 batch_size = GetTensorDim(grad_out->shape(), FORMAT_NHWC, 'N'); in launch() [all …]
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D | mkl_conv_ops.cc | 431 const int64 stride_n = GetTensorDim(strides_, data_format_, 'N'); in MklConvOp() 432 const int64 stride_c = GetTensorDim(strides_, data_format_, 'C'); in MklConvOp() 478 : GetTensorDim(input, data_format_, 'C'); in Compute() 490 : GetTensorDim(input, data_format_, 'H'); in Compute() 502 : GetTensorDim(input, data_format_, 'W'); in Compute() 513 : GetTensorDim(input, data_format_, 'N'); in Compute() 522 const int stride_rows = GetTensorDim(strides_, data_format_, 'H'); in Compute() 523 const int stride_cols = GetTensorDim(strides_, data_format_, 'W'); in Compute() 875 const int64 stride_n = GetTensorDim(strides_, data_format_, 'N'); in MklConvOp() 876 const int64 stride_c = GetTensorDim(strides_, data_format_, 'C'); in MklConvOp() [all …]
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D | avgpooling_op.cc | 134 const int32 ksize_n = GetTensorDim(ksize_, data_format_, 'N'); in AvgPoolingOp() 135 const int32 stride_n = GetTensorDim(stride_, data_format_, 'N'); in AvgPoolingOp() 394 const int32 ksize_n = GetTensorDim(ksize_, data_format_, 'N'); in AvgPoolingGradOp() 395 const int32 stride_n = GetTensorDim(stride_, data_format_, 'N'); in AvgPoolingGradOp() 474 const int32 ksize_n = GetTensorDim(ksize_, data_format_, 'N'); in AvgPoolingGradOpCustomGPUKernel() 475 const int32 stride_n = GetTensorDim(stride_, data_format_, 'N'); in AvgPoolingGradOpCustomGPUKernel()
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D | fused_batch_norm_op.cc | 252 const int64 batch_size = GetTensorDim(x, tensor_format, 'N'); in operator ()() 253 const int64 channels = GetTensorDim(x, tensor_format, 'C'); in operator ()() 254 const int64 height = GetTensorDim(x, tensor_format, 'H'); in operator ()() 255 const int64 width = GetTensorDim(x, tensor_format, 'W'); in operator ()() 393 const int64 batch_size = GetTensorDim(x, tensor_format, 'N'); in operator ()() 394 const int64 channels = GetTensorDim(x, tensor_format, 'C'); in operator ()() 395 const int64 height = GetTensorDim(x, tensor_format, 'H'); in operator ()() 396 const int64 width = GetTensorDim(x, tensor_format, 'W'); in operator ()()
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D | conv_ops_fused_impl.h | 581 const int64 in_batch = GetTensorDim(input, params.data_format, 'N'); 582 int64 in_rows = GetTensorDim(input, params.data_format, 'H'); 583 int64 in_cols = GetTensorDim(input, params.data_format, 'W'); 584 const int64 in_depths = GetTensorDim(input, params.data_format, 'C'); 592 const int64 out_batch = GetTensorDim(*output, params.data_format, 'N'); 593 const int64 out_rows = GetTensorDim(*output, params.data_format, 'H'); 594 const int64 out_cols = GetTensorDim(*output, params.data_format, 'W'); 595 const int64 out_depths = GetTensorDim(*output, params.data_format, 'C');
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D | conv_ops_fused_image_transform.cc | 636 const int64 stride_n = GetTensorDim(strides_, FORMAT_NHWC, 'N'); in FusedResizeConv2DUsingGemmOp() 637 const int64 stride_c = GetTensorDim(strides_, FORMAT_NHWC, 'C'); in FusedResizeConv2DUsingGemmOp() 822 const int stride_rows = GetTensorDim(strides_, FORMAT_NHWC, 'H'); in Compute() 823 const int stride_cols = GetTensorDim(strides_, FORMAT_NHWC, 'W'); in Compute()
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D | mkl_fused_batch_norm_op.cc | 727 depth_ = static_cast<int>(GetTensorDim(input, tensor_format_, 'C')); in ExtractParams() 1049 depth_ = static_cast<int>(GetTensorDim(input, tensor_format_, 'C')); in ExtractParams()
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/external/tensorflow/tensorflow/core/util/ |
D | tensor_format.h | 425 T GetTensorDim(gtl::ArraySlice<T> dimension_attributes, in GetTensorDim() function 448 T GetTensorDim(const std::vector<T>& attributes, TensorFormat format, in GetTensorDim() function 450 return GetTensorDim(gtl::ArraySlice<T>(attributes), format, dimension); in GetTensorDim() 455 inline int64 GetTensorDim(const TensorShape& tensor_shape, in GetTensorDim() function 457 return GetTensorDim(gtl::ArraySlice<int64>(tensor_shape.dim_sizes()), in GetTensorDim() 472 inline int64 GetTensorDim(const Tensor& tensor, TensorFormat tensor_format, in GetTensorDim() function 474 return GetTensorDim(tensor.shape(), tensor_format, dimension); in GetTensorDim() 584 const int64 batch = GetTensorDim(src_shape, src_format, 'N'); in ShapeFromFormat() 585 const int64 channels = GetTensorDim(src_shape, src_format, 'C') * in ShapeFromFormat()
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/external/tensorflow/tensorflow/contrib/fused_conv/kernels/ |
D | fused_conv2d_bias_activation_op.cc | 115 stride_rows_ = GetTensorDim(strides, data_format_, 'H'); in FusedConv2DBiasActivationOp() 116 stride_cols_ = GetTensorDim(strides, data_format_, 'W'); in FusedConv2DBiasActivationOp() 119 (GetTensorDim(strides, data_format_, 'N') == 1 && in FusedConv2DBiasActivationOp() 120 GetTensorDim(strides, data_format_, 'C') == 1), in FusedConv2DBiasActivationOp() 207 const int32 batch_size = GetTensorDim(conv_input, data_format_, 'N'); in Compute() 208 const int32 conv_input_rows = GetTensorDim(conv_input, data_format_, 'H'); in Compute() 209 const int32 conv_input_cols = GetTensorDim(conv_input, data_format_, 'W'); in Compute() 470 const int batch_size = GetTensorDim(conv_input_param, data_format, 'N'); in launch() 471 int conv_input_rows = GetTensorDim(conv_input_param, data_format, 'H'); in launch() 472 int conv_input_cols = GetTensorDim(conv_input_param, data_format, 'W'); in launch() [all …]
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/external/tensorflow/tensorflow/core/framework/ |
D | common_shape_fns.cc | 464 const int32 stride_rows = GetTensorDim(strides, data_format, 'H'); in Conv2DShapeImpl() 465 const int32 stride_cols = GetTensorDim(strides, data_format, 'W'); in Conv2DShapeImpl() 466 const int32 dilation_rows = GetTensorDim(dilations, data_format, 'H'); in Conv2DShapeImpl() 467 const int32 dilation_cols = GetTensorDim(dilations, data_format, 'W'); in Conv2DShapeImpl() 753 int32 stride_rows = GetTensorDim(strides, data_format, 'H'); in AvgPoolShape() 754 int32 stride_cols = GetTensorDim(strides, data_format, 'W'); in AvgPoolShape() 755 int32 kernel_rows = GetTensorDim(kernel_sizes, data_format, 'H'); in AvgPoolShape() 756 int32 kernel_cols = GetTensorDim(kernel_sizes, data_format, 'W'); in AvgPoolShape() 903 int32 stride_depth = GetTensorDim(strides, data_format, 'C'); in MaxPoolShape() 904 int32 stride_rows = GetTensorDim(strides, data_format, 'H'); in MaxPoolShape() [all …]
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