From 8ce9d88f930cecd55eb73ea5e8ce749090002aa8 Mon Sep 17 00:00:00 2001 From: "Guo, Yejun" <yejun.guo@intel.com> Date: Sat, 11 Apr 2020 13:46:47 +0800 Subject: [PATCH] dnn/native: add native support for divide it can be tested with model file generated with below python script: import tensorflow as tf import numpy as np import imageio in_img = imageio.imread('input.jpg') 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') z1 = 2 / x z2 = 1 / z1 z3 = z2 / 0.25 + 0.3 z4 = z3 - x * 1.5 - 0.3 y = tf.identity(z4, 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: Guo, Yejun <yejun.guo@intel.com> --- .../dnn/dnn_backend_native_layer_mathbinary.c | 17 +++++++++++++++++ .../dnn/dnn_backend_native_layer_mathbinary.h | 1 + tools/python/convert_from_tensorflow.py | 5 +++-- tools/python/convert_header.py | 2 +- 4 files changed, 22 insertions(+), 3 deletions(-) diff --git a/libavfilter/dnn/dnn_backend_native_layer_mathbinary.c b/libavfilter/dnn/dnn_backend_native_layer_mathbinary.c index 222941e952047..c32a0427884a8 100644 --- a/libavfilter/dnn/dnn_backend_native_layer_mathbinary.c +++ b/libavfilter/dnn/dnn_backend_native_layer_mathbinary.c @@ -133,6 +133,23 @@ int dnn_execute_layer_math_binary(DnnOperand *operands, const int32_t *input_ope } } return 0; + case DMBO_REALDIV: + 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 index d58b48c7471b3..2ffbb66eebcdb 100644 --- a/libavfilter/dnn/dnn_backend_native_layer_mathbinary.h +++ b/libavfilter/dnn/dnn_backend_native_layer_mathbinary.h @@ -34,6 +34,7 @@ typedef enum { DMBO_SUB = 0, DMBO_ADD = 1, DMBO_MUL = 2, + DMBO_REALDIV = 3, DMBO_COUNT } DNNMathBinaryOperation; diff --git a/tools/python/convert_from_tensorflow.py b/tools/python/convert_from_tensorflow.py index dc3b4e381d4f1..a0fdad25b7d5d 100644 --- a/tools/python/convert_from_tensorflow.py +++ b/tools/python/convert_from_tensorflow.py @@ -71,7 +71,7 @@ def __init__(self, graph_def, nodes, outfile, dump4tb): self.conv2d_scope_names = set() self.conv2d_scopename_inputname_dict = {} self.op2code = {'Conv2D':1, 'DepthToSpace':2, 'MirrorPad':3, 'Maximum':4, 'MathBinary':5} - self.mathbin2code = {'Sub':0, 'Add':1, 'Mul':2} + self.mathbin2code = {'Sub':0, 'Add':1, 'Mul':2, 'RealDiv':3} self.mirrorpad_mode = {'CONSTANT':0, 'REFLECT':1, 'SYMMETRIC':2} self.name_operand_dict = {} @@ -311,7 +311,8 @@ def dump_layers_to_file(self, f): self.dump_mathbinary_to_file(node, f) elif node.op == 'Mul': self.dump_mathbinary_to_file(node, f) - + elif node.op == 'RealDiv': + self.dump_mathbinary_to_file(node, f) def dump_operands_to_file(self, f): operands = sorted(self.name_operand_dict.values()) diff --git a/tools/python/convert_header.py b/tools/python/convert_header.py index 87899fe72c6a5..75d1ce803c535 100644 --- a/tools/python/convert_header.py +++ b/tools/python/convert_header.py @@ -23,4 +23,4 @@ major = 1 # increase minor when we don't have to re-convert the model file -minor = 3 +minor = 4