| /external/tensorflow/tensorflow/compiler/tf2xla/kernels/ |
| D | image_ops.cc | 112 int channel_dim = input_shape.dims() - 1; in Compile() local
150 int channel_dim = input_shape.dims() - 1; in Compile() local
190 int channel_dim = input_shape.dims() - 1; in Compile() local
240 const int channel_dim = input_shape.dims() - 1; in Compile() local
294 const int channel_dim = input_shape.dims() - 1; in Compile() local
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| /external/tensorflow/tensorflow/core/kernels/ |
| D | bias_op.cc | 57 int32_t channel_dim = value_tensor.dims() - 1; in GetBiasValueDims() local
113 int channel_dim; in Compute() local
186 int channel_dim; in Compute() local
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| /external/XNNPACK/src/subgraph/ |
| D | hardswish.c | 39 …const size_t channel_dim = num_input_dims == 0 ? 1 : values[input_id].shape.dim[num_input_dims - 1… in create_hardswish_operator() local
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| D | floor.c | 37 …const size_t channel_dim = num_input_dims == 0 ? 1 : values[input_id].shape.dim[num_input_dims - 1… in create_floor_operator() local
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| D | negate.c | 37 …const size_t channel_dim = num_input_dims == 0 ? 1 : values[input_id].shape.dim[num_input_dims - 1… in create_negate_operator() local
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| D | square-root.c | 39 …const size_t channel_dim = num_input_dims == 0 ? 1 : values[input_id].shape.dim[num_input_dims - 1… in create_square_root_operator() local
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| D | softmax.c | 38 const size_t channel_dim = values[input_id].shape.dim[num_input_dims - 1]; in create_softmax_operator() local
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| D | bankers-rounding.c | 37 …const size_t channel_dim = num_input_dims == 0 ? 1 : values[input_id].shape.dim[num_input_dims - 1… in create_bankers_rounding_operator() local
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| D | square.c | 37 …const size_t channel_dim = num_input_dims == 0 ? 1 : values[input_id].shape.dim[num_input_dims - 1… in create_square_operator() local
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| D | ceiling.c | 37 …const size_t channel_dim = num_input_dims == 0 ? 1 : values[input_id].shape.dim[num_input_dims - 1… in create_ceiling_operator() local
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| D | abs.c | 36 …const size_t channel_dim = num_input_dims == 0 ? 1 : values[input_id].shape.dim[num_input_dims - 1… in create_abs_operator() local
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| D | sigmoid.c | 37 …const size_t channel_dim = num_input_dims == 0 ? 1 : values[input_id].shape.dim[num_input_dims - 1… in create_sigmoid_operator() local
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| D | elu.c | 37 …const size_t channel_dim = num_input_dims == 0 ? 1 : values[input_id].shape.dim[num_input_dims - 1… in create_elu_operator() local
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| D | prelu.c | 40 …const size_t channel_dim = num_input_dims == 0 ? 1 : values[input_id].shape.dim[num_input_dims - 1… in create_prelu_operator() local
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| D | leaky-relu.c | 37 …const size_t channel_dim = num_input_dims == 0 ? 1 : values[input_id].shape.dim[num_input_dims - 1… in create_leaky_relu_operator() local
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| D | static-resize-bilinear-2d.c | 36 const size_t channel_dim = values[input_id].shape.dim[3]; in create_resize_bilinear_operator() local
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| D | average-pooling-2d.c | 35 const size_t channel_dim = values[input_id].shape.dim[3]; in create_average_pooling_operator() local
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| D | argmax-pooling-2d.c | 41 const size_t channel_dim = values[input_id].shape.dim[3]; in create_argmax_pooling_operator() local
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| D | clamp.c | 38 …const size_t channel_dim = num_input_dims == 0 ? 1 : values[input_id].shape.dim[num_input_dims - 1… in create_clamp_operator() local
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| D | unpooling-2d.c | 40 const size_t channel_dim = values[input_value_id].shape.dim[3]; in create_unpooling_operator() local
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| D | convert.c | 38 …const size_t channel_dim = num_input_dims == 0 ? 1 : values[input_id].shape.dim[num_input_dims - 1… in create_convert_operator() local
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| D | max-pooling-2d.c | 37 const size_t channel_dim = values[input_id].shape.dim[3]; in create_max_pooling_operator() local
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| D | global-average-pooling.c | 39 const size_t channel_dim = values[input_id].shape.dim[num_input_dims - 1]; in create_global_average_pooling_operator() local
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| /external/tensorflow/tensorflow/lite/kernels/ |
| D | dequantize_test.cc | 126 int channel_dim, int version) { in DequantizePerChannelOpModel()
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| /external/XNNPACK/src/ |
| D | tensor.c | 171 size_t channel_dim, in xnn_define_channelwise_quantized_tensor_value()
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