From f73cc61bf5aa383048979f4de2023877c522f6be Mon Sep 17 00:00:00 2001 From: Ting Fu Date: Mon, 25 May 2020 22:46:26 +0800 Subject: [PATCH] dnn_backend_native_layer_mathunary: add abs support more math unary operations will be added here It can be tested with the model file generated with below python scripy: import tensorflow as tf import numpy as np import imageio in_img = imageio.imread('input.jpeg') in_img = in_img.astype(np.float32)/255.0 in_data = in_img[np.newaxis, :] x = tf.placeholder(tf.float32, shape=[1, None, None, 3], name='dnn_in') x1 = tf.subtract(x, 0.5) x2 = tf.abs(x1) y = tf.identity(x2, name='dnn_out') sess=tf.Session() sess.run(tf.global_variables_initializer()) graph_def = tf.graph_util.convert_variables_to_constants(sess, sess.graph_def, ['dnn_out']) tf.train.write_graph(graph_def, '.', 'image_process.pb', as_text=False) print("image_process.pb generated, please use \ path_to_ffmpeg/tools/python/convert.py to generate image_process.model\n") output = sess.run(y, feed_dict={x: in_data}) imageio.imsave("out.jpg", np.squeeze(output)) Signed-off-by: Ting Fu Signed-off-by: Guo, Yejun --- libavfilter/dnn/Makefile | 1 + libavfilter/dnn/dnn_backend_native.h | 1 + .../dnn/dnn_backend_native_layer_mathunary.c | 80 +++++++++++++++++++ .../dnn/dnn_backend_native_layer_mathunary.h | 45 +++++++++++ libavfilter/dnn/dnn_backend_native_layers.c | 2 + tools/python/convert_from_tensorflow.py | 16 +++- tools/python/convert_header.py | 2 +- 7 files changed, 145 insertions(+), 2 deletions(-) create mode 100644 libavfilter/dnn/dnn_backend_native_layer_mathunary.c create mode 100644 libavfilter/dnn/dnn_backend_native_layer_mathunary.h diff --git a/libavfilter/dnn/Makefile b/libavfilter/dnn/Makefile index ce529587e1..bb37298b58 100644 --- a/libavfilter/dnn/Makefile +++ b/libavfilter/dnn/Makefile @@ -6,6 +6,7 @@ OBJS-$(CONFIG_DNN) += dnn/dnn_backend_native_layer_con OBJS-$(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 +OBJS-$(CONFIG_DNN) += dnn/dnn_backend_native_layer_mathunary.o DNN-OBJS-$(CONFIG_LIBTENSORFLOW) += dnn/dnn_backend_tf.o diff --git a/libavfilter/dnn/dnn_backend_native.h b/libavfilter/dnn/dnn_backend_native.h index 5d76d87915..61f0cb202f 100644 --- a/libavfilter/dnn/dnn_backend_native.h +++ b/libavfilter/dnn/dnn_backend_native.h @@ -42,6 +42,7 @@ typedef enum { DLT_MIRROR_PAD = 3, DLT_MAXIMUM = 4, DLT_MATH_BINARY = 5, + DLT_MATH_UNARY = 6, DLT_COUNT } DNNLayerType; diff --git a/libavfilter/dnn/dnn_backend_native_layer_mathunary.c b/libavfilter/dnn/dnn_backend_native_layer_mathunary.c new file mode 100644 index 0000000000..d65af151cd --- /dev/null +++ b/libavfilter/dnn/dnn_backend_native_layer_mathunary.c @@ -0,0 +1,80 @@ +/* + * 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_mathunary.h" + +int dnn_load_layer_math_unary(Layer *layer, AVIOContext *model_file_context, int file_size) +{ + DnnLayerMathUnaryParams *params; + int dnn_size = 0; + params = av_malloc(sizeof(*params)); + if(!params) + return 0; + + params->un_op = (int32_t)avio_rl32(model_file_context); + dnn_size += 4; + layer->params = params; + layer->input_operand_indexes[0] = (int32_t)avio_rl32(model_file_context); + layer->output_operand_index = (int32_t)avio_rl32(model_file_context); + dnn_size += 8; + + return dnn_size; + +} + +int dnn_execute_layer_math_unary(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 DnnLayerMathUnaryParams *params = (const DnnLayerMathUnaryParams *)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->un_op) { + case DMUO_ABS: + for (int i = 0; i < dims_count; ++i) + dst[i] = FFABS(src[i]); + return 0; + default: + return -1; + } +} diff --git a/libavfilter/dnn/dnn_backend_native_layer_mathunary.h b/libavfilter/dnn/dnn_backend_native_layer_mathunary.h new file mode 100644 index 0000000000..4e44003b66 --- /dev/null +++ b/libavfilter/dnn/dnn_backend_native_layer_mathunary.h @@ -0,0 +1,45 @@ +/* + * 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_MATHUNARY_H +#define AVFILTER_DNN_DNN_BACKEND_NATIVE_LAYER_MATHUNARY_H + +#include "libavformat/avio.h" +#include "dnn_backend_native.h" + +typedef enum { + DMUO_ABS = 0, + DMUO_COUNT +} DNNMathUnaryOperation; + +typedef struct DnnLayerMathUnaryParams{ + DNNMathUnaryOperation un_op; +} DnnLayerMathUnaryParams; + +int dnn_load_layer_math_unary(Layer *layer, AVIOContext *model_file_context, int file_size); +int dnn_execute_layer_math_unary(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 af18552eb4..70f9a5f958 100644 --- a/libavfilter/dnn/dnn_backend_native_layers.c +++ b/libavfilter/dnn/dnn_backend_native_layers.c @@ -25,6 +25,7 @@ #include "dnn_backend_native_layer_depth2space.h" #include "dnn_backend_native_layer_maximum.h" #include "dnn_backend_native_layer_mathbinary.h" +#include "dnn_backend_native_layer_mathunary.h" LayerFunc layer_funcs[DLT_COUNT] = { {NULL, NULL}, @@ -33,4 +34,5 @@ LayerFunc layer_funcs[DLT_COUNT] = { {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}, + {dnn_execute_layer_math_unary, dnn_load_layer_math_unary}, }; diff --git a/tools/python/convert_from_tensorflow.py b/tools/python/convert_from_tensorflow.py index 1c20891fcc..8c0a9be7be 100644 --- a/tools/python/convert_from_tensorflow.py +++ b/tools/python/convert_from_tensorflow.py @@ -70,8 +70,9 @@ 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, 'MathBinary':5} + self.op2code = {'Conv2D':1, 'DepthToSpace':2, 'MirrorPad':3, 'Maximum':4, 'MathBinary':5, 'MathUnary':6} self.mathbin2code = {'Sub':0, 'Add':1, 'Mul':2, 'RealDiv':3, 'Minimum':4} + self.mathun2code = {'Abs':0} self.mirrorpad_mode = {'CONSTANT':0, 'REFLECT':1, 'SYMMETRIC':2} self.name_operand_dict = {} @@ -286,6 +287,17 @@ class TFConverter: np.array([output_operand_index], dtype=np.uint32).tofile(f) + def dump_mathunary_to_file(self, node, f): + self.layer_number = self.layer_number + 1 + self.converted_nodes.add(node.name) + i0_node = self.name_node_dict[node.input[0]] + np.array([self.op2code['MathUnary'], self.mathun2code[node.op]], 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) + 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: @@ -307,6 +319,8 @@ class TFConverter: self.dump_maximum_to_file(node, f) elif node.op in self.mathbin2code: self.dump_mathbinary_to_file(node, f) + elif node.op in self.mathun2code: + self.dump_mathunary_to_file(node, f) def dump_operands_to_file(self, f): diff --git a/tools/python/convert_header.py b/tools/python/convert_header.py index e692a5e217..ad4491729a 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 = 5 +minor = 6 -- GitLab