From ffa1561608f513b3a5d3d1568f75126f21bce663 Mon Sep 17 00:00:00 2001 From: "Guo, Yejun" Date: Fri, 20 Mar 2020 20:55:38 +0800 Subject: [PATCH] dnn_backend_native_layer_mathbinary: add sub support more math binary operations will be added here Signed-off-by: Guo, Yejun --- libavfilter/dnn/Makefile | 1 + libavfilter/dnn/dnn_backend_native.h | 1 + .../dnn/dnn_backend_native_layer_mathbinary.c | 113 ++++++++++++++++++ .../dnn/dnn_backend_native_layer_mathbinary.h | 49 ++++++++ libavfilter/dnn/dnn_backend_native_layers.c | 2 + tools/python/convert_from_tensorflow.py | 55 ++++++++- tools/python/convert_header.py | 2 +- 7 files changed, 219 insertions(+), 4 deletions(-) create mode 100644 libavfilter/dnn/dnn_backend_native_layer_mathbinary.c create mode 100644 libavfilter/dnn/dnn_backend_native_layer_mathbinary.h diff --git a/libavfilter/dnn/Makefile b/libavfilter/dnn/Makefile index 171f00e502..ce529587e1 100644 --- a/libavfilter/dnn/Makefile +++ b/libavfilter/dnn/Makefile @@ -5,6 +5,7 @@ OBJS-$(CONFIG_DNN) += dnn/dnn_backend_native_layer_pad OBJS-$(CONFIG_DNN) += dnn/dnn_backend_native_layer_conv2d.o OBJS-$(CONFIG_DNN) += dnn/dnn_backend_native_layer_depth2space.o OBJS-$(CONFIG_DNN) += dnn/dnn_backend_native_layer_maximum.o +OBJS-$(CONFIG_DNN) += dnn/dnn_backend_native_layer_mathbinary.o DNN-OBJS-$(CONFIG_LIBTENSORFLOW) += dnn/dnn_backend_tf.o diff --git a/libavfilter/dnn/dnn_backend_native.h b/libavfilter/dnn/dnn_backend_native.h index 53ed22c5e2..5d76d87915 100644 --- a/libavfilter/dnn/dnn_backend_native.h +++ b/libavfilter/dnn/dnn_backend_native.h @@ -41,6 +41,7 @@ typedef enum { DLT_DEPTH_TO_SPACE = 2, DLT_MIRROR_PAD = 3, DLT_MAXIMUM = 4, + DLT_MATH_BINARY = 5, DLT_COUNT } DNNLayerType; diff --git a/libavfilter/dnn/dnn_backend_native_layer_mathbinary.c b/libavfilter/dnn/dnn_backend_native_layer_mathbinary.c new file mode 100644 index 0000000000..3b8bab82bc --- /dev/null +++ b/libavfilter/dnn/dnn_backend_native_layer_mathbinary.c @@ -0,0 +1,113 @@ +/* + * Copyright (c) 2020 + * + * This file is part of FFmpeg. + * + * FFmpeg is free software; you can redistribute it and/or + * modify it under the terms of the GNU Lesser General Public + * License as published by the Free Software Foundation; either + * version 2.1 of the License, or (at your option) any later version. + * + * FFmpeg is distributed in the hope that it will be useful, + * but WITHOUT ANY WARRANTY; without even the implied warranty of + * MERCHANTABILITY or FITNESS FOR A PARTICULAR PURPOSE. See the GNU + * Lesser General Public License for more details. + * + * You should have received a copy of the GNU Lesser General Public + * License along with FFmpeg; if not, write to the Free Software + * Foundation, Inc., 51 Franklin Street, Fifth Floor, Boston, MA 02110-1301 USA + */ + +/** + * @file + * DNN native backend implementation. + */ + +#include "dnn_backend_native.h" +#include "libavutil/avassert.h" +#include "dnn_backend_native_layer_mathbinary.h" + +int dnn_load_layer_math_binary(Layer *layer, AVIOContext *model_file_context, int file_size) +{ + DnnLayerMathBinaryParams *params; + int dnn_size = 0; + int input_index = 0; + params = av_malloc(sizeof(*params)); + if (!params) + return 0; + + params->bin_op = (int32_t)avio_rl32(model_file_context); + dnn_size += 4; + + params->input0_broadcast = (int32_t)avio_rl32(model_file_context); + dnn_size += 4; + if (params->input0_broadcast) { + params->v = av_int2float(avio_rl32(model_file_context)); + } else { + layer->input_operand_indexes[input_index] = (int32_t)avio_rl32(model_file_context); + input_index++; + } + dnn_size += 4; + + params->input1_broadcast = (int32_t)avio_rl32(model_file_context); + dnn_size += 4; + if (params->input1_broadcast) { + params->v = av_int2float(avio_rl32(model_file_context)); + } else { + layer->input_operand_indexes[input_index] = (int32_t)avio_rl32(model_file_context); + input_index++; + } + dnn_size += 4; + + layer->output_operand_index = (int32_t)avio_rl32(model_file_context); + dnn_size += 4; + layer->params = params; + + return dnn_size; +} + +int dnn_execute_layer_math_binary(DnnOperand *operands, const int32_t *input_operand_indexes, + int32_t output_operand_index, const void *parameters) +{ + const DnnOperand *input = &operands[input_operand_indexes[0]]; + DnnOperand *output = &operands[output_operand_index]; + const DnnLayerMathBinaryParams *params = (const DnnLayerMathBinaryParams *)parameters; + int dims_count; + const float *src; + float *dst; + + for (int i = 0; i < 4; ++i) + output->dims[i] = input->dims[i]; + + output->data_type = input->data_type; + output->length = calculate_operand_data_length(output); + output->data = av_realloc(output->data, output->length); + if (!output->data) + return DNN_ERROR; + + dims_count = calculate_operand_dims_count(output); + src = input->data; + dst = output->data; + + switch (params->bin_op) { + case DMBO_SUB: + if (params->input0_broadcast) { + for (int i = 0; i < dims_count; ++i) { + dst[i] = params->v - src[i]; + } + } else if (params->input1_broadcast) { + for (int i = 0; i < dims_count; ++i) { + dst[i] = src[i] - params->v; + } + } else { + const DnnOperand *input1 = &operands[input_operand_indexes[1]]; + const float *src1 = input1->data; + for (int i = 0; i < dims_count; ++i) { + dst[i] = src[i] - src1[i]; + } + } + return 0; + default: + return -1; + } +} diff --git a/libavfilter/dnn/dnn_backend_native_layer_mathbinary.h b/libavfilter/dnn/dnn_backend_native_layer_mathbinary.h new file mode 100644 index 0000000000..6b684d1165 --- /dev/null +++ b/libavfilter/dnn/dnn_backend_native_layer_mathbinary.h @@ -0,0 +1,49 @@ +/* + * Copyright (c) 2020 + * + * This file is part of FFmpeg. + * + * FFmpeg is free software; you can redistribute it and/or + * modify it under the terms of the GNU Lesser General Public + * License as published by the Free Software Foundation; either + * version 2.1 of the License, or (at your option) any later version. + * + * FFmpeg is distributed in the hope that it will be useful, + * but WITHOUT ANY WARRANTY; without even the implied warranty of + * MERCHANTABILITY or FITNESS FOR A PARTICULAR PURPOSE. See the GNU + * Lesser General Public License for more details. + * + * You should have received a copy of the GNU Lesser General Public + * License along with FFmpeg; if not, write to the Free Software + * Foundation, Inc., 51 Franklin Street, Fifth Floor, Boston, MA 02110-1301 USA + */ + +/** + * @file + * DNN inference functions interface for native backend. + */ + + +#ifndef AVFILTER_DNN_DNN_BACKEND_NATIVE_LAYER_MATHBINARY_H +#define AVFILTER_DNN_DNN_BACKEND_NATIVE_LAYER_MATHBINARY_H + +#include "libavformat/avio.h" +#include "dnn_backend_native.h" + +typedef enum { + DMBO_SUB = 0, + DMBO_COUNT +} DNNMathBinaryOperation; + +typedef struct DnnLayerMathBinaryParams{ + DNNMathBinaryOperation bin_op; + int input0_broadcast; + int input1_broadcast; + float v; +} DnnLayerMathBinaryParams; + +int dnn_load_layer_math_binary(Layer *layer, AVIOContext *model_file_context, int file_size); +int dnn_execute_layer_math_binary(DnnOperand *operands, const int32_t *input_operand_indexes, + int32_t output_operand_index, const void *parameters); + +#endif diff --git a/libavfilter/dnn/dnn_backend_native_layers.c b/libavfilter/dnn/dnn_backend_native_layers.c index d659667de1..af18552eb4 100644 --- a/libavfilter/dnn/dnn_backend_native_layers.c +++ b/libavfilter/dnn/dnn_backend_native_layers.c @@ -24,6 +24,7 @@ #include "dnn_backend_native_layer_conv2d.h" #include "dnn_backend_native_layer_depth2space.h" #include "dnn_backend_native_layer_maximum.h" +#include "dnn_backend_native_layer_mathbinary.h" LayerFunc layer_funcs[DLT_COUNT] = { {NULL, NULL}, @@ -31,4 +32,5 @@ LayerFunc layer_funcs[DLT_COUNT] = { {dnn_execute_layer_depth2space, dnn_load_layer_depth2space}, {dnn_execute_layer_pad, dnn_load_layer_pad}, {dnn_execute_layer_maximum, dnn_load_layer_maximum}, + {dnn_execute_layer_math_binary, dnn_load_layer_math_binary}, }; diff --git a/tools/python/convert_from_tensorflow.py b/tools/python/convert_from_tensorflow.py index 5e87e227ea..2485f16cd6 100644 --- a/tools/python/convert_from_tensorflow.py +++ b/tools/python/convert_from_tensorflow.py @@ -70,7 +70,8 @@ class TFConverter: self.converted_nodes = set() self.conv2d_scope_names = set() self.conv2d_scopename_inputname_dict = {} - self.op2code = {'Conv2D':1, 'DepthToSpace':2, 'MirrorPad':3, 'Maximum':4} + self.op2code = {'Conv2D':1, 'DepthToSpace':2, 'MirrorPad':3, 'Maximum':4, 'MathBinary':5} + self.mathbin2code = {'Sub':0} self.mirrorpad_mode = {'CONSTANT':0, 'REFLECT':1, 'SYMMETRIC':2} self.name_operand_dict = {} @@ -113,6 +114,8 @@ class TFConverter: # if activation is None, and BiasAdd.next is the last op which is Identity if conv2d_scope_name + '/BiasAdd' in self.edges: anode = self.edges[conv2d_scope_name + '/BiasAdd'][0] + if anode.op not in self.conv_activations: + anode = None else: anode = None return knode, bnode, dnode, anode @@ -252,14 +255,47 @@ class TFConverter: np.array([input_operand_index, output_operand_index], dtype=np.uint32).tofile(f) + def dump_sub_to_file(self, node, f): + assert(node.op == 'Sub') + self.layer_number = self.layer_number + 1 + self.converted_nodes.add(node.name) + i0_node = self.name_node_dict[node.input[0]] + i1_node = self.name_node_dict[node.input[1]] + np.array([self.op2code['MathBinary'], self.mathbin2code[node.op]], dtype=np.uint32).tofile(f) + if i0_node.op == 'Const': + scalar = i0_node.attr['value'].tensor.float_val[0] + assert(i0_node.name.find('sub/x')) + np.array([1], dtype=np.uint32).tofile(f) + np.array([scalar], dtype=np.float32).tofile(f) + np.array([0], dtype=np.uint32).tofile(f) + input_operand_index = self.add_operand(i1_node.name, Operand.IOTYPE_INPUT) + np.array([input_operand_index], dtype=np.uint32).tofile(f) + elif i1_node.op == 'Const': + scalar = i1_node.attr['value'].tensor.float_val[0] + assert(i1_node.name.find('sub/y')) + np.array([0], dtype=np.uint32).tofile(f) + input_operand_index = self.add_operand(i0_node.name, Operand.IOTYPE_INPUT) + np.array([input_operand_index], dtype=np.uint32).tofile(f) + np.array([1], dtype=np.uint32).tofile(f) + np.array([scalar], dtype=np.float32).tofile(f) + else: + np.array([0], dtype=np.uint32).tofile(f) + input_operand_index = self.add_operand(i0_node.name, Operand.IOTYPE_INPUT) + np.array([input_operand_index], dtype=np.uint32).tofile(f) + np.array([0], dtype=np.uint32).tofile(f) + input_operand_index = self.add_operand(i1_node.name, Operand.IOTYPE_INPUT) + np.array([input_operand_index], dtype=np.uint32).tofile(f) + output_operand_index = self.add_operand(node.name, Operand.IOTYPE_OUTPUT) + np.array([output_operand_index], dtype=np.uint32).tofile(f) + + def dump_layers_to_file(self, f): for node in self.nodes: if node.name in self.converted_nodes: continue # conv2d with dilation generates very complex nodes, so handle it in special - scope_name = TFConverter.get_scope_name(node.name) - if scope_name in self.conv2d_scope_names: + if self.in_conv2d_scope(node.name): if node.op == 'Conv2D': self.dump_complex_conv2d_to_file(node, f) continue @@ -272,6 +308,8 @@ class TFConverter: self.dump_mirrorpad_to_file(node, f) elif node.op == 'Maximum': self.dump_maximum_to_file(node, f) + elif node.op == 'Sub': + self.dump_sub_to_file(node, f) def dump_operands_to_file(self, f): @@ -352,6 +390,17 @@ class TFConverter: return name[0:index] + def in_conv2d_scope(self, name): + inner_scope = TFConverter.get_scope_name(name) + if inner_scope == "": + return False; + for scope in self.conv2d_scope_names: + index = inner_scope.find(scope) + if index == 0: + return True + return False + + def generate_conv2d_scope_info(self): # mostly, conv2d is a sub block in graph, get the scope name for node in self.nodes: diff --git a/tools/python/convert_header.py b/tools/python/convert_header.py index 67672b2785..6576fca7a1 100644 --- a/tools/python/convert_header.py +++ b/tools/python/convert_header.py @@ -23,4 +23,4 @@ str = 'FFMPEGDNNNATIVE' major = 1 # increase minor when we don't have to re-convert the model file -minor = 0 +minor = 1