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Searched refs:GetTensorDim (Results 1 – 25 of 26) sorted by relevance

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/external/tensorflow/tensorflow/core/kernels/
Dmkl_conv_ops.h76 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()
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Dpooling_ops_3d.cc63 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()
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Dconv_ops_3d.cc87 (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()
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Dmkl_pooling_ops_common.cc234 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()
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Dconv_grad_ops_3d.cc188 (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()
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Dpooling_ops_3d_sycl.h186 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');
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Dconv_ops.cc141 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()
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Dpooling_ops_common.cc61 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()
Dcudnn_pooling_gpu.cc44 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()
Dconv_grad_input_ops.cc590 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()
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Dconv_grad_filter_ops.cc453 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()
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Dconv_ops_using_gemm.cc444 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()
Dmkl_conv_grad_bias_ops.cc83 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()
Ddepthwise_conv_op.cc277 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()
Ddepthwise_conv_grad_op.cc70 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()
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Dmaxpooling_op.cc365 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()
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Dmkl_conv_ops.cc431 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()
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Davgpooling_op.cc134 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()
Dfused_batch_norm_op.cc252 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 ()()
Dconv_ops_fused_impl.h581 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');
Dconv_ops_fused_image_transform.cc636 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()
Dmkl_fused_batch_norm_op.cc727 depth_ = static_cast<int>(GetTensorDim(input, tensor_format_, 'C')); in ExtractParams()
1049 depth_ = static_cast<int>(GetTensorDim(input, tensor_format_, 'C')); in ExtractParams()
/external/tensorflow/tensorflow/core/util/
Dtensor_format.h425 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()
/external/tensorflow/tensorflow/contrib/fused_conv/kernels/
Dfused_conv2d_bias_activation_op.cc115 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()
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/external/tensorflow/tensorflow/core/framework/
Dcommon_shape_fns.cc464 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()
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