/external/tensorflow/tensorflow/core/kernels/ |
H A D | resize_nearest_neighbor_op_gpu.cu.cc | 37 const int nthreads, const T* bottom_data, const int in_height, 50 const T* bottom_data_n = bottom_data + n * channels * in_height * in_width; 54 in_height - 1); 66 const int nthreads, const T* top_diff, const int in_height, 76 int in_y = n % in_height; 77 n /= in_height; 104 const int64 in_height = input.dimension(1); local 117 output_size, input.data(), in_height, in_width, channels, 138 const int64 in_height = input.dimension(1); local 152 const int input_size = batch_size * channels * in_height * in_widt 36 ResizeNearestNeighborNHWC( const int nthreads, const T* bottom_data, const int in_height, const int in_width, const int channels, const int out_height, const int out_width, const float height_scale, const float width_scale, T* top_data) argument 65 ResizeNearestNeighborBackwardNHWC( const int nthreads, const T* top_diff, const int in_height, const int in_width, const int channels, const int out_height, const int out_width, const float height_scale, const float width_scale, T* bottom_diff) argument [all...] |
H A D | resize_bilinear_op_gpu.cu.cc | 38 int batch, int in_height, int in_width, 54 (in_y < in_height - 1) ? ceilf(in_y) : in_height - 1; 64 images[((b * in_height + top_y_index) * in_width + left_x_index) * 68 images[((b * in_height + top_y_index) * in_width + right_x_index) * 72 images[((b * in_height + bottom_y_index) * in_width + left_x_index) * 76 images[((b * in_height + bottom_y_index) * in_width + right_x_index) * 156 const int in_height = images.dimension(1); local 170 width_scale, batch, in_height, in_width, channels, out_height, 36 ResizeBilinearKernel(const int32 nthreads, const T* images, float height_scale, float width_scale, int batch, int in_height, int in_width, int channels, int out_height, int out_width, float* output) argument
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H A D | resize_nearest_neighbor_op.cc | 52 OP_REQUIRES(context, st.in_height < (1 << 24) && st.in_width < (1 << 24), 92 const int64 in_height = input.dimension(1); local 104 in_height - 1); 148 const int64 in_height = input.dim_size(1); variable 169 CalculateResizeScale(out_height, in_height, align_corners_); 203 const int64 in_height = input.dimension(1); local 212 for (int y = 0; y < in_height; ++y) {
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H A D | quantized_resize_bilinear_op_test.cc | 109 const int64 in_height, const int64 in_width, 118 GetReferenceWeight(out_height, in_height, 1, y, height_scale); 121 const int64 in_batch_num_values = in_height * in_row_size; 144 const int64 in_height, const int64 in_width, 151 CalculateResizeScale(in_height, out_height, align_corners); 160 in_data, batch_size, in_height, in_width, out_height, out_width, 280 /*in_height=*/IN_WIDTH, 289 void RunTestResizeBilinearTwoDims(int batch_size, int in_height, int in_width, argument 294 const float max = batch_size * in_height * in_width * channels / RATIO; 297 batch_size, in_height, in_widt 108 CalcReferenceResizedVal(const T* image_data, const int batch_size, const int64 in_height, const int64 in_width, const int64 out_height, const int64 out_width, const int channels, const float height_scale, const float width_scale, const float min, const float max, const int b, const int64 x, const int64 y, const int c) argument 143 CheckTensorValue(const T* in_data, const T* out_data, const int batch_size, const int64 in_height, const int64 in_width, const int64 out_height, const int64 out_width, const int channels, const bool align_corners, const float min, const float max, const float tolerance, const bool relative) argument 309 RunBenchmarkResizeBilinearTwoDims(int batch_size, int in_height, int in_width, int out_height, int out_width, int channels, int iteration) argument [all...] |
H A D | resize_area_op_test.cc | 63 const int64 in_height = input_data.dimension(1); local 73 const float height_scale = in_height / static_cast<float>(out_height); 129 static_cast<float>(input_data(b, BOUND(i, in_height), 145 void RunRandomTest(int in_height, int in_width, int target_height, argument 148 SetRandomImageInput(TensorShape({1, in_height, in_width, channels}));
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H A D | depthwise_conv_op_gpu.cu.cc | 75 const int in_height = args.in_rows; local 110 const int input_offset_temp = in_height * batch; 112 input_row_end < in_height && input_col_end < in_width) { 139 if (in_row >= 0 && in_row < in_height && in_col >= 0 && 179 const int in_height = args.in_rows; 197 const int in_size = in_height * in_row_size; 201 const int even_height = kKnownEvenHeight || (1 & ~in_height); 202 const int tile_height = in_height + filter_height - even_height; 244 !kKnownEvenHeight && thread_row + (in_height & 1) == block_height; 311 const int in_height [all...] |
H A D | image_resizer_state.h | 80 in_height = static_cast<int32>(input.dim_size(1)); 91 height_scale = CalculateResizeScale(in_height, out_height, align_corners_); 121 int64 in_height; member in struct:tensorflow::ImageResizerState
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H A D | resize_bicubic_op_test.cc | 113 const int64 in_height = images.dimension(1); local 123 const float height_scale = in_height / static_cast<float>(out_height); 131 GetWeightsAndIndices(height_scale, y, in_height, &y_weights, 158 void RunRandomTest(const int batch_size, const int64 in_height, argument 161 LOG(INFO) << "Running random test " << in_height << "x" << in_width << "x" 165 TensorShape({batch_size, in_height, in_width, channels}));
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H A D | resize_bilinear_op.cc | 105 const int64 in_height, const int64 in_width, const int64 out_height, 112 const int batch_size, const int64 in_height, 119 const int64 in_batch_num_values = in_height * in_row_size; 208 const int64 in_height = images.dimension(1); local 216 if (out_height == in_height && out_width == in_width) { 225 compute_interpolation_weights(out_height, in_height, height_scale, 235 resize_image<T>(images, batch_size, in_height, in_width, out_height, 111 resize_image(typename TTypes<T, 4>::ConstTensor images, const int batch_size, const int64 in_height, const int64 in_width, const int64 out_height, const int64 out_width, const int channels, const std::vector<CachedInterpolation>& xs_vec, const std::vector<CachedInterpolation>& ys, typename TTypes<float, 4>::Tensor output) argument
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H A D | quantized_resize_bilinear_op.cc | 462 const int batch_size, const int64 in_height, 473 BuildLerpCache<float>(out_height, in_height, height_scale, 1, 0); 476 const int64 in_batch_num_values = in_height * in_row_size; 510 const int batch_size, const int64 in_height, 516 ResizeImageReference<T>(images, batch_size, in_height, in_width, out_height, 523 const int batch_size, const int64 in_height, 538 BuildLerpCache<int32>(out_height, in_height, height_scale, 1, RESOLUTION); 541 const int64 in_batch_num_values = in_height * in_row_size; 584 const int batch_size, const int64 in_height, 599 BuildLerpCache<int16>(out_height, in_height, height_scal 461 ResizeImageReference(typename TTypes<T, 4>::ConstTensor images, const int batch_size, const int64 in_height, const int64 in_width, const int64 out_height, const int64 out_width, const int channels, const float height_scale, const float width_scale, const float in_min, const float in_max, typename TTypes<T, 4>::Tensor* output) argument 509 ResizeImage(typename TTypes<T, 4>::ConstTensor images, const int batch_size, const int64 in_height, const int64 in_width, const int64 out_height, const int64 out_width, const int channels, const float height_scale, const float width_scale, const float in_min, const float in_max, typename TTypes<T, 4>::Tensor* output) argument 522 ResizeImage(typename TTypes<qint32, 4>::ConstTensor images, const int batch_size, const int64 in_height, const int64 in_width, const int64 out_height, const int64 out_width, const int channels, const float height_scale, const float width_scale, const float in_min, const float in_max, typename TTypes<qint32, 4>::Tensor* output) argument 583 ResizeImage(typename TTypes<quint8, 4>::ConstTensor images, const int batch_size, const int64 in_height, const int64 in_width, const int64 out_height, const int64 out_width, const int channels, const float height_scale, const float width_scale, const float in_min, const float in_max, typename TTypes<quint8, 4>::Tensor* output) argument 653 const int64 in_height = images.dimension(1); local [all...] |
H A D | ops_util_test.cc | 33 int in_height; member in struct:tensorflow::__anon26535::OpsUtilTest::padding_struct::__anon26536 73 pad_struct.input.in_height, pad_struct.input.filter_height, 88 pad_struct.input.in_height, pad_struct.input.filter_height, 107 pad_struct.input.in_height, pad_struct.input.filter_height,
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H A D | resize_bilinear_op_test.cc | 68 const int64 in_height = images.dimension(1); local 78 const float height_scale = in_height / static_cast<float>(out_height); 86 std::min(static_cast<int64>(ceilf(in_y)), in_height - 1);
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H A D | resize_area_op.cc | 239 input_ptr + (b * st.in_height * st.in_width * st.channels + 240 Bound(i, st.in_height) * st.in_width * st.channels));
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H A D | resize_bicubic_op.cc | 234 const int64 in_batch_width = resizer_state.in_height * in_row_width; 246 resizer_state.in_height, &y_wai);
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H A D | conv_ops_fused.cc | 196 std::min(static_cast<int64>(std::ceil(in_y)), (st.in_height - 1)); 661 st.in_height = input.dim_size(1);
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/external/webrtc/webrtc/modules/video_render/android/java/src/org/webrtc/videoengine/ |
H A D | ViESurfaceRenderer.java | 61 int in_width, int in_height) { 64 changeDestRect(in_width, in_height); 67 " in_width:" + in_width + " in_height:" + in_height + 60 surfaceChanged(SurfaceHolder holder, int format, int in_width, int in_height) argument
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/external/webrtc/talk/media/base/ |
H A D | videoadapter.cc | 260 VideoFormat VideoAdapter::AdaptFrameResolution(int in_width, int in_height) { argument 265 in_width, in_height, input_format_.interval, input_format_.fourcc)); 296 << "x" << in_height 305 in_width, in_height, output_num_pixels_); 307 const int output_height = static_cast<int>(in_height * scale + .5f); 335 << "x" << in_height
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H A D | videocommon.cc | 211 void ComputeScaleToSquarePixels(int in_width, int in_height, argument 215 *scaled_height = in_height * pixel_height / pixel_width;
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H A D | videoadapter.h | 63 VideoFormat AdaptFrameResolution(int in_width, int in_height);
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H A D | videocommon.h | 176 void ComputeScaleToSquarePixels(int in_width, int in_height,
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H A D | videoadapter_unittest.cc | 98 const int in_height = abs(captured_frame->height); local 100 video_adapter_->AdaptFrameResolution(in_width, in_height); 104 in_height == adapted_format.height);
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/external/tensorflow/tensorflow/python/kernel_tests/ |
H A D | depthtospace_op_test.py | 230 def compareToTranspose(self, batch_size, in_height, in_width, out_channels, 233 nhwc_input_shape = [batch_size, in_height, in_width, in_channels] 234 nchw_input_shape = [batch_size, in_channels, in_height, in_width]
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H A D | spacetodepth_op_test.py | 229 in_height = out_height * block_size 231 nhwc_input_shape = [batch_size, in_height, in_width, in_channels] 232 nchw_input_shape = [batch_size, in_channels, in_height, in_width]
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/external/webrtc/webrtc/video/ |
H A D | send_statistics_proxy.cc | 98 int in_height = input_height_counter_.Avg(kMinRequiredSamples); local 104 in_height);
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/external/tensorflow/tensorflow/python/ops/ |
H A D | nn_ops.py | 1142 format. Its shape is `[batch, in_height, in_width, in_channels]`. 1276 format. Its shape is `[batch, in_height, in_width, in_channels]`. 1373 in_height = output_shape[1] + pad_top + pad_bottom 1377 pad_bottom_extra = (rate - in_height % rate) % rate 1388 rate * rate * output_shape[0], (in_height + pad_bottom_extra) // rate, 2566 The `value` tensor has shape `[batch, in_height, in_width, depth]` and the 2587 value: A `Tensor`. 4-D with shape `[batch, in_height, in_width, depth]`.
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