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Searched refs:filter_width (Results 1 – 25 of 51) sorted by relevance

123

/external/tensorflow/tensorflow/core/kernels/
Dconv_ops_using_gemm.cc91 int filter_width, int filter_count, int stride_rows, in operator ()() argument
112 ((output_width - 1) * stride_cols + filter_width - input_width + 1) / in operator ()()
119 ((output_width - 1) * stride_cols + filter_width - input_width) / 2; in operator ()()
156 for (int filter_x = 0; filter_x < filter_width; ++filter_x) { in operator ()()
175 filter_data[(filter_y * filter_width * input_depth * in operator ()()
214 int filter_width, int filter_count, int stride_rows, in operator ()() argument
224 if ((filter_width <= 0) || (filter_height <= 0) || (filter_count <= 0)) { in operator ()()
226 << filter_width << ", " << filter_height << ", " in operator ()()
238 if (filter_height == 1 && filter_width == 1 && stride_rows == 1 && in operator ()()
251 } else if (filter_height == input_height && filter_width == input_width && in operator ()()
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Ddepthwise_conv_op_gpu.cu.cc80 const int filter_width = in DepthwiseConv2dGPUKernelNHWC() local
106 const int input_col_end = input_col_start + filter_width; in DepthwiseConv2dGPUKernelNHWC()
116 const int filter_offset_temp = filter_width * filter_row; in DepthwiseConv2dGPUKernelNHWC()
117 UNROLL for (int filter_col = 0; filter_col < filter_width; in DepthwiseConv2dGPUKernelNHWC()
135 const int filter_offset_temp = filter_width * filter_row; in DepthwiseConv2dGPUKernelNHWC()
136 UNROLL for (int filter_col = 0; filter_col < filter_width; in DepthwiseConv2dGPUKernelNHWC()
184 const int filter_width = in DepthwiseConv2dGPUKernelNHWCSmall() local
199 const int filter_pixels = filter_height * filter_width; in DepthwiseConv2dGPUKernelNHWCSmall()
200 const int tile_width = in_width + filter_width - 1; in DepthwiseConv2dGPUKernelNHWCSmall()
277 UNROLL for (int c = 0; c < filter_width; ++c) { in DepthwiseConv2dGPUKernelNHWCSmall()
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Dquantized_conv_ops.cc57 int filter_height, int filter_width, int filter_count, in operator ()() argument
91 ((output_width - 1) * stride + filter_width - input_width + 1) / 2; in operator ()()
96 ((output_width - 1) * stride + filter_width - input_width) / 2; in operator ()()
133 for (int filter_x = 0; filter_x < filter_width; ++filter_x) { in operator ()()
156 filter_data[(filter_y * filter_width * input_depth * in operator ()()
203 int filter_height, int filter_width, int filter_count, in operator ()() argument
224 filter_height, filter_width, filter_count, filter_offset, in operator ()()
236 ((output_width - 1) * stride + filter_width - input_width + 1) / 2; in operator ()()
241 ((output_width - 1) * stride + filter_width - input_width) / 2; in operator ()()
257 const int filter_value_count = filter_width * filter_height * input_depth; in operator ()()
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Dconv_ops_fused.cc261 const T2* filter_data, int filter_height, int filter_width, in operator ()() argument
274 if ((filter_width <= 0) || (filter_height <= 0) || (filter_count <= 0)) { in operator ()()
276 << filter_width << ", " << filter_height << ", " in operator ()()
296 ((output_width - 1) * stride_cols + filter_width - padded_width + 1) / in operator ()()
303 ((output_width - 1) * stride_cols + filter_width - padded_width) / 2; in operator ()()
331 const int filter_value_count = filter_width * filter_height * input_depth; in operator ()()
368 filter_width; in operator ()()
550 (filter_y * filter_width * task_params.input_depth); in operator ()()
567 (filter_width * task_params.input_depth), in operator ()()
Dops_util_test.cc36 int filter_width; member
78 pad_struct.input.in_width, pad_struct.input.filter_width, in VerifyGet2dOutputSizeBoundaries()
93 pad_struct.input.in_width, pad_struct.input.filter_width, in VerifyGet2dOutputSizeValues()
112 pad_struct.input.in_width, pad_struct.input.filter_width, in VerifyGet2dOutputVerboseSizeValues()
/external/tensorflow/tensorflow/contrib/lite/kernels/internal/optimized/
Dmultithreaded_conv.h118 const T* filter_data, int filter_height, int filter_width, in operator()
124 const bool is_1x1_kernel = (filter_height == 1 && filter_width == 1 && in operator()
137 } else if (filter_height == input_height && filter_width == input_width && in operator()
142 filter_width * filter_height * input_depth; in operator()
155 ConstEigenTensor filter(filter_data, filter_height, filter_width, in operator()
178 const int filter_width = ArraySize(filter_dims, 1); in Conv() local
183 input_depth, filter_data, filter_height, filter_width, in Conv()
Dcblas_conv.h46 const int filter_width = ArraySize(filter_dims, 1); in Conv() local
49 filter_width != 1 || filter_height != 1; in Conv()
53 pad_width, pad_height, filter_height, filter_width, 0, in Conv()
Ddepthwiseconv_float.h766 int depth_multiplier, int filter_width,
788 for (int filter_x = 0; filter_x < filter_width; ++filter_x) {
839 int pad_width, int depth_multiplier, int filter_width,
870 for (int filter_x = 0; filter_x < filter_width; ++filter_x) {
925 const int filter_width = ArraySize(filter_dims, 1);
1020 pad_width, depth_multiplier, filter_width,
/external/tensorflow/tensorflow/contrib/lite/kernels/
Dpooling.cc93 computeOutSize(width, params->filter_width, params->stride_width); in GenericPrepare()
100 params->filter_width, outWidth); in GenericPrepare()
133 params->filter_width, params->filter_height, activation_min, \ in AverageEvalFloat()
155 params->filter_width, params->filter_height, \ in AverageEvalQuantized()
177 params->filter_width, params->filter_height, activation_min, \ in MaxEvalFloat()
199 params->filter_width, params->filter_height, activation_min, \ in MaxEvalQuantized()
221 params->filter_width, params->filter_height, activation_min, \ in L2EvalFloat()
Dconv.cc155 int filter_width = filter->dims->data[2]; in Prepare() local
170 int outWidth = computeOutSize(width, filter_width, params->stride_width); in Prepare()
176 ComputePadding(params->stride_width, width, filter_width, outWidth); in Prepare()
207 filter_width != 1 || filter_height != 1); in Prepare()
241 im2col_size->data[3] = input_depth * filter_height * filter_width; in Prepare()
260 hwcn_weights_size->data[0] = (filter_height * filter_width * input_depth); in Prepare()
Dpooling_test.cc32 int filter_width, int filter_height, in BasePoolingOpModel() argument
39 CreatePool2DOptions(builder_, Padding_VALID, 2, 2, filter_width, in BasePoolingOpModel()
Ddepthwise_conv.cc124 int filter_width = SizeOfDimension(filter, 2); in Prepare() local
139 int out_width = compute_out_size(width, filter_width, params->stride_width); in Prepare()
146 ComputePadding(params->stride_width, width, filter_width, out_width); in Prepare()
/external/tensorflow/tensorflow/core/api_def/base_api/
Dapi_def_Conv2D.pbtxt14 `[filter_height, filter_width, in_channels, out_channels]`
62 `[filter_height, filter_width, in_channels, out_channels]`, this op
66 `[filter_height * filter_width * in_channels, output_channels]`.
69 filter_height * filter_width * in_channels]`.
Dapi_def_Dilation2DBackpropFilter.pbtxt12 3-D with shape `[filter_height, filter_width, depth]`.
24 3-D with shape `[filter_height, filter_width, depth]`.
Dapi_def_Dilation2D.pbtxt12 3-D with shape `[filter_height, filter_width, depth]`.
44 `filter` tensor has shape `[filter_height, filter_width, depth]`, i.e., each
Dapi_def_Conv2DBackpropFilter.pbtxt14 `[filter_height, filter_width, in_channels, out_channels]` tensor.
28 `[filter_height, filter_width, in_channels, out_channels]`. Gradient w.r.t.
Dapi_def_DepthwiseConv2dNativeBackpropFilter.pbtxt16 `[filter_height, filter_width, in_channels, depthwise_multiplier]` tensor.
32 `[filter_height, filter_width, in_channels, out_channels]`. Gradient w.r.t.
/external/tensorflow/tensorflow/tools/graph_transforms/
Dflatten_atrous.cc71 const int32 filter_width = filter.dim_size(1); in FlattenAtrousConv() local
78 (filter_width - 1) * block_width + 1; in FlattenAtrousConv()
89 for (int w = 0; w < filter_width; ++w) { in FlattenAtrousConv()
/external/tensorflow/tensorflow/contrib/lite/kernels/internal/reference/
Dreference_ops.h176 const int filter_width = ArraySize(filter_dims, 1); in Conv() local
187 for (int filter_x = 0; filter_x < filter_width; ++filter_x) { in Conv()
270 const int filter_width = ArraySize(filter_dims, 1); in Conv() local
281 for (int filter_x = 0; filter_x < filter_width; ++filter_x) { in Conv()
1687 int pad_height, int filter_width, int filter_height, in AveragePool() argument
1707 std::min(filter_width, input_width - in_x_origin); in AveragePool()
1738 int pad_height, int filter_width, int filter_height, in AveragePool() argument
1743 pad_height, filter_width, filter_height, output_activation_min, in AveragePool()
1750 int pad_width, int pad_height, int filter_width, in AveragePool() argument
1754 filter_width, filter_height, output_data, output_dims); in AveragePool()
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Ddepthwiseconv_float.h39 const int filter_width = ArraySize(filter_dims, 1); in DepthwiseConv() local
54 for (int filter_x = 0; filter_x < filter_width; ++filter_x) { in DepthwiseConv()
Ddepthwiseconv_uint8.h45 const int filter_width = ArraySize(filter_dims, 1); in DepthwiseConv() local
60 for (int filter_x = 0; filter_x < filter_width; ++filter_x) { in DepthwiseConv()
/external/tensorflow/tensorflow/contrib/kfac/python/ops/
Dfisher_factors.py949 filter_height, filter_width, in_channels, out_channels = self._filter_shape
951 filter_height * filter_width * in_channels + self._has_bias,
965 filter_height, filter_width, _, _ = self._filter_shape
971 ksizes=[1, filter_height, filter_width, 1],
1096 filter_height, filter_width, in_channels, _ = self._filter_shape
1097 size = filter_height * filter_width * in_channels + self._has_bias
1113 filter_height, filter_width, in_channels, _ = self._filter_shape
1119 ksizes=[1, filter_height, filter_width, 1],
1124 flatten_size = (filter_height * filter_width * in_channels)
/external/tensorflow/tensorflow/core/kernels/neon/
Ddepthwiseconv_float.h428 int depth_multiplier, int filter_width,
450 for (int filter_x = 0; filter_x < filter_width; ++filter_x) {
501 int pad_width, int depth_multiplier, int filter_width,
512 for (int filter_x = 0; filter_x < filter_width; ++filter_x) {
570 const int filter_width = ArraySize(filter_dims, 1);
654 pad_width, depth_multiplier, filter_width,
/external/tensorflow/tensorflow/python/ops/
Dnn_ops.py1348 filter_height, filter_width = filter_shape[0], filter_shape[1]
1353 filter_width_up = filter_width + (filter_width - 1) * (rate - 1)
2138 filter_width = int(filter_shape[1])
2143 (output_count * filter_in_depth * filter_height * filter_width * 2))
2157 filter_width = int(filter_shape[1])
2159 return ops.OpStats("flops", (output_count * filter_height * filter_width * 2))
2557 filter_width = int(filter_shape[1])
2559 return ops.OpStats("flops", (output_count * filter_height * filter_width * 2))
/external/tensorflow/tensorflow/tools/benchmark/
Dbenchmark_model.cc201 int64 filter_width = filter_shape.dim_size(1); in CalculateFlops() local
205 output_count * filter_in_depth * filter_height * filter_width * 2; in CalculateFlops()
222 int64 filter_width = filter_shape.dim_size(1); in CalculateFlops() local
224 current_flops = output_count * filter_height * filter_width * 2; in CalculateFlops()

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