// Copyright 2020 Google LLC // // This source code is licensed under the BSD-style license found in the // LICENSE file in the root directory of this source tree. #include #include #include #include #include #include #include enum xnn_status xnn_define_depthwise_convolution_2d( xnn_subgraph_t subgraph, uint32_t input_padding_top, uint32_t input_padding_right, uint32_t input_padding_bottom, uint32_t input_padding_left, uint32_t kernel_height, uint32_t kernel_width, uint32_t subsampling_height, uint32_t subsampling_width, uint32_t dilation_height, uint32_t dilation_width, uint32_t depth_multiplier, size_t input_channels, float output_min, float output_max, uint32_t input_id, uint32_t filter_id, uint32_t bias_id, uint32_t output_id, uint32_t flags) { if ((xnn_params.init_flags & XNN_INIT_FLAG_XNNPACK) == 0) { xnn_log_error("failed to define %s operator: XNNPACK is not initialized", xnn_node_type_to_string(xnn_node_type_depthwise_convolution_2d)); return xnn_status_uninitialized; } if (kernel_width == 0 || kernel_height == 0) { xnn_log_error( "failed to define %s operator with %" PRIu32 "x%" PRIu32 " kernel: kernel dimensions must be non-zero", xnn_node_type_to_string(xnn_node_type_depthwise_convolution_2d), kernel_width, kernel_height); return xnn_status_invalid_parameter; } if (subsampling_width == 0 || subsampling_height == 0) { xnn_log_error( "failed to define %s operator with %" PRIu32 "x%" PRIu32 " subsampling: subsampling dimensions must be non-zero", xnn_node_type_to_string(xnn_node_type_depthwise_convolution_2d), subsampling_width, subsampling_height); return xnn_status_invalid_parameter; } if (dilation_width == 0 || dilation_height == 0) { xnn_log_error( "failed to define %s operator with %" PRIu32 "x%" PRIu32 " dilation: dilation dimensions must be non-zero", xnn_node_type_to_string(xnn_node_type_depthwise_convolution_2d), dilation_width, dilation_height); return xnn_status_invalid_parameter; } if (depth_multiplier == 0) { xnn_log_error( "failed to define %s operator with %" PRIu32 " depth multiplier: depth multiplier must be non-zero", xnn_node_type_to_string(xnn_node_type_depthwise_convolution_2d), depth_multiplier); return xnn_status_invalid_parameter; } if (input_channels == 0) { xnn_log_error( "failed to define %s operator with %zu input channels: number of channels must be non-zero", xnn_node_type_to_string(xnn_node_type_depthwise_convolution_2d), input_channels); return xnn_status_invalid_parameter; } if (isnan(output_min)) { xnn_log_error( "failed to define %s operator with NaN output lower bound: lower bound must be non-NaN", xnn_node_type_to_string(xnn_node_type_depthwise_convolution_2d)); return xnn_status_invalid_parameter; } if (isnan(output_max)) { xnn_log_error( "failed to define %s operator with NaN output upper bound: upper bound must be non-NaN", xnn_node_type_to_string(xnn_node_type_depthwise_convolution_2d)); return xnn_status_invalid_parameter; } if (output_min >= output_max) { xnn_log_error( "failed to define %s operator with [%.7g, %.7g] output range: lower bound must be below upper bound", xnn_node_type_to_string(xnn_node_type_depthwise_convolution_2d), output_min, output_max); return xnn_status_invalid_parameter; } const uint32_t supported_flags = XNN_FLAG_TENSORFLOW_SAME_PADDING; const uint32_t invalid_flags = flags & ~supported_flags; if (invalid_flags != 0) { xnn_log_error( "failed to define %s operator with 0x%08" PRIx32 " flags: invalid flags 0x%08" PRIx32, xnn_node_type_to_string(xnn_node_type_depthwise_convolution_2d), flags, invalid_flags); return xnn_status_invalid_parameter; } const bool any_padding = (input_padding_left | input_padding_top | input_padding_right | input_padding_bottom) != 0; if ((flags & XNN_FLAG_TENSORFLOW_SAME_PADDING) != 0 && any_padding) { xnn_log_error( "failed to define %s operator with %" PRIu32 "+%" PRIu32 "x%" PRIu32 "+%" PRIu32" padding: " "TensorFlow SAME padding can't be combined with explicit padding specification", xnn_node_type_to_string(xnn_node_type_convolution_2d), input_padding_top, input_padding_left, input_padding_bottom, input_padding_right); return xnn_status_invalid_parameter; } // Convert TensorFlow SAME padding to explicit padding specification whenever possible if ((flags & XNN_FLAG_TENSORFLOW_SAME_PADDING) != 0 && (subsampling_height | subsampling_width) == 1) { flags &= ~XNN_FLAG_TENSORFLOW_SAME_PADDING; const uint32_t padding_height = (kernel_height - 1) * dilation_height; const uint32_t padding_width = (kernel_width - 1) * dilation_width; input_padding_left = padding_width / 2; input_padding_top = padding_height / 2; input_padding_right = padding_width - input_padding_left; input_padding_bottom = padding_height - input_padding_top; } if (input_id >= subgraph->num_values) { xnn_log_error( "failed to define %s operator with input ID #%" PRIu32 ": invalid Value ID", xnn_node_type_to_string(xnn_node_type_depthwise_convolution_2d), input_id); return xnn_status_invalid_parameter; } if (filter_id >= subgraph->num_values) { xnn_log_error( "failed to define %s operator with filter ID #%" PRIu32 ": invalid Value ID", xnn_node_type_to_string(xnn_node_type_depthwise_convolution_2d), filter_id); return xnn_status_invalid_parameter; } if (bias_id >= subgraph->num_values) { xnn_log_error( "failed to define %s operator with bias ID #%" PRIu32 ": invalid Value ID", xnn_node_type_to_string(xnn_node_type_depthwise_convolution_2d), bias_id); return xnn_status_invalid_parameter; } if (output_id >= subgraph->num_values) { xnn_log_error( "failed to define %s operator with output ID #%" PRIu32 ": invalid Value ID", xnn_node_type_to_string(xnn_node_type_depthwise_convolution_2d), output_id); return xnn_status_invalid_parameter; } struct xnn_node* node = xnn_subgraph_new_node(subgraph); if (node == NULL) { return xnn_status_out_of_memory; } node->type = xnn_node_type_depthwise_convolution_2d; node->params.depthwise_convolution_2d.input_padding_top = input_padding_top; node->params.depthwise_convolution_2d.input_padding_right = input_padding_right; node->params.depthwise_convolution_2d.input_padding_bottom = input_padding_bottom; node->params.depthwise_convolution_2d.input_padding_left = input_padding_left; node->params.depthwise_convolution_2d.kernel_height = kernel_height; node->params.depthwise_convolution_2d.kernel_width = kernel_width; node->params.depthwise_convolution_2d.subsampling_height = subsampling_height; node->params.depthwise_convolution_2d.subsampling_width = subsampling_width; node->params.depthwise_convolution_2d.dilation_height = dilation_height; node->params.depthwise_convolution_2d.dilation_width = dilation_width; node->params.depthwise_convolution_2d.depth_multiplier = depth_multiplier; node->params.depthwise_convolution_2d.input_channels = input_channels; node->activation.output_min = output_min; node->activation.output_max = output_max; node->num_inputs = 3; node->inputs[0] = input_id; node->inputs[1] = filter_id; node->inputs[2] = bias_id; node->num_outputs = 1; node->outputs[0] = output_id; node->flags = flags; return xnn_status_success; };