/external/tensorflow/tensorflow/core/api_def/base_api/ |
D | api_def_Conv3DBackpropInputV2.pbtxt | 8 `[batch, depth, rows, cols, in_channels]` tensor. 14 Shape `[depth, rows, cols, in_channels, out_channels]`. 15 `in_channels` must match between `input` and `filter`. 43 [batch, in_depth, in_height, in_width, in_channels]. 45 [batch, in_channels, in_depth, in_height, in_width].
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D | api_def_Conv3D.pbtxt | 6 Shape `[batch, in_depth, in_height, in_width, in_channels]`. 12 Shape `[filter_depth, filter_height, filter_width, in_channels, 13 out_channels]`. `in_channels` must match between `input` and `filter`. 34 [batch, in_depth, in_height, in_width, in_channels]. 36 [batch, in_channels, in_depth, in_height, in_width].
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D | api_def_DepthwiseConv2dNative.pbtxt | 38 Given an input tensor of shape `[batch, in_height, in_width, in_channels]` 40 `[filter_height, filter_width, in_channels, channel_multiplier]`, containing 41 `in_channels` convolutional filters of depth 1, `depthwise_conv2d` applies 44 together. Thus, the output has `in_channels * channel_multiplier` channels. 47 for k in 0..in_channels-1
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D | api_def_Conv2DBackpropFilter.pbtxt | 6 4-D with shape `[batch, in_height, in_width, in_channels]`. 14 `[filter_height, filter_width, in_channels, out_channels]` tensor. 28 `[filter_height, filter_width, in_channels, out_channels]`. Gradient w.r.t. 60 [batch, in_height, in_width, in_channels]. 62 [batch, in_channels, in_height, in_width].
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D | api_def_Conv3DBackpropFilterV2.pbtxt | 6 Shape `[batch, depth, rows, cols, in_channels]`. 14 `[filter_depth, filter_height, filter_width, in_channels, out_channels]` 43 [batch, in_depth, in_height, in_width, in_channels]. 45 [batch, in_channels, in_depth, in_height, in_width].
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D | api_def_Conv3DBackpropInput.pbtxt | 6 Shape `[batch, depth, rows, cols, in_channels]`. 12 Shape `[depth, rows, cols, in_channels, out_channels]`. 13 `in_channels` must match between `input` and `filter`.
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D | api_def_Conv3DBackpropFilter.pbtxt | 6 Shape `[batch, depth, rows, cols, in_channels]`. 12 Shape `[depth, rows, cols, in_channels, out_channels]`. 13 `in_channels` must match between `input` and `filter`.
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D | api_def_Conv2D.pbtxt | 14 `[filter_height, filter_width, in_channels, out_channels]` 69 Given an input tensor of shape `[batch, in_height, in_width, in_channels]` 71 `[filter_height, filter_width, in_channels, out_channels]`, this op 75 `[filter_height * filter_width * in_channels, output_channels]`. 78 filter_height * filter_width * in_channels]`.
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D | api_def_Conv2DBackpropInput.pbtxt | 14 `[filter_height, filter_width, in_channels, out_channels]`. 27 4-D with shape `[batch, in_height, in_width, in_channels]`. Gradient 59 [batch, in_height, in_width, in_channels]. 61 [batch, in_channels, in_height, in_width].
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D | api_def_DepthwiseConv2dNativeBackpropFilter.pbtxt | 8 in_width, in_channels]` tensor. 16 `[filter_height, filter_width, in_channels, depthwise_multiplier]` tensor. 32 `[filter_height, filter_width, in_channels, out_channels]`. Gradient w.r.t.
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D | api_def_MaxPool.pbtxt | 39 [batch, in_height, in_width, in_channels]. 41 [batch, in_channels, in_height, in_width].
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D | api_def_MaxPoolV2.pbtxt | 39 [batch, in_height, in_width, in_channels]. 41 [batch, in_channels, in_height, in_width].
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D | api_def_BiasAddGrad.pbtxt | 22 [batch, in_channels, in_height, in_width]. 23 The tensor will be added to "in_channels", the third-to-the-last
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D | api_def_BiasAdd.pbtxt | 28 [batch, in_channels, in_height, in_width]. 29 The tensor will be added to "in_channels", the third-to-the-last
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D | api_def_MaxPool3D.pbtxt | 40 [batch, in_depth, in_height, in_width, in_channels]. 42 [batch, in_channels, in_depth, in_height, in_width].
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D | api_def_AvgPool3D.pbtxt | 40 [batch, in_depth, in_height, in_width, in_channels]. 42 [batch, in_channels, in_depth, in_height, in_width].
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D | api_def_AvgPool.pbtxt | 38 [batch, in_height, in_width, in_channels]. 40 [batch, in_channels, in_height, in_width].
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D | api_def_MaxPoolGradGrad.pbtxt | 51 [batch, in_height, in_width, in_channels]. 53 [batch, in_channels, in_height, in_width].
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D | api_def_MaxPool3DGrad.pbtxt | 46 [batch, in_depth, in_height, in_width, in_channels]. 48 [batch, in_channels, in_depth, in_height, in_width].
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D | api_def_AvgPool3DGrad.pbtxt | 46 [batch, in_depth, in_height, in_width, in_channels]. 48 [batch, in_channels, in_depth, in_height, in_width].
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D | api_def_MaxPoolGradGradV2.pbtxt | 51 [batch, in_height, in_width, in_channels]. 53 [batch, in_channels, in_height, in_width].
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D | api_def_MaxPoolGradV2.pbtxt | 51 [batch, in_height, in_width, in_channels]. 53 [batch, in_channels, in_height, in_width].
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/external/tensorflow/tensorflow/core/kernels/ |
D | eigen_spatial_convolutions_test.cc | 668 const int in_channels = 10; in TEST() local 682 Tensor<float, 4> input(in_channels, in_depth, in_rows, in_cols); in TEST() 683 Tensor<float, 5> kernel(kern_filters, in_channels, kern_depth, kern_height, in TEST() 709 for (int id = 0; id < in_channels; ++id) { in TEST() 729 const int in_channels = 10; in TEST() local 743 Tensor<float, 4, RowMajor> input(in_cols, in_rows, in_depth, in_channels); in TEST() 745 in_channels, kern_filters); in TEST() 771 for (int id = 0; id < in_channels; ++id) { in TEST() 791 const int in_channels = 10; in TEST() local 805 Tensor<float, 4> input(in_channels, in_depth, in_rows, in_cols); in TEST() [all …]
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/external/webrtc/webrtc/common_audio/ |
D | lapped_transform_unittest.cc | 28 size_t in_channels, in ProcessAudioBlock() argument 32 RTC_CHECK_EQ(in_channels, out_channels); in ProcessAudioBlock() 52 size_t in_channels, in ProcessAudioBlock() argument 56 RTC_CHECK_EQ(in_channels, out_channels); in ProcessAudioBlock()
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/external/tensorflow/tensorflow/tools/graph_transforms/ |
D | flatten_atrous.cc | 71 const int32 in_channels = filter.dim_size(2); in FlattenAtrousConv() local 81 in_channels, out_channels})); in FlattenAtrousConv() 89 for (int c_in = 0; c_in < in_channels; ++c_in) { in FlattenAtrousConv()
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