From c0cdeea0ee2c4af9fb4948fe3e33b857cf6d2771 Mon Sep 17 00:00:00 2001 From: Ting Fu Date: Mon, 29 Jun 2020 22:54:10 +0800 Subject: [PATCH] dnn_backend_native_layer_mathunary: add atanh support It can be tested with the model generated with below python script: 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') please uncomment the part you want to test x_sinh_1 = tf.sinh(x) x_out = tf.divide(x_sinh_1, 1.176) # sinh(1.0) x_cosh_1 = tf.cosh(x) x_out = tf.divide(x_cosh_1, 1.55) # cosh(1.0) x_tanh_1 = tf.tanh(x) x__out = tf.divide(x_tanh_1, 0.77) # tanh(1.0) x_asinh_1 = tf.asinh(x) x_out = tf.divide(x_asinh_1, 0.89) # asinh(1.0/1.1) x_acosh_1 = tf.add(x, 1.1) x_acosh_2 = tf.acosh(x_acosh_1) # accept (1, inf) x_out = tf.divide(x_acosh_2, 1.4) # acosh(2.1) x_atanh_1 = tf.divide(x, 1.1) x_atanh_2 = tf.atanh(x_atanh_1) # accept (-1, 1) x_out = tf.divide(x_atanh_2, 1.55) # atanhh(1.0/1.1) y = tf.identity(x_out, name='dnn_out') #please only preserve the x_out you want to test 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 --- libavfilter/dnn/dnn_backend_native_layer_mathunary.c | 4 ++++ libavfilter/dnn/dnn_backend_native_layer_mathunary.h | 1 + tools/python/convert_from_tensorflow.py | 2 +- tools/python/convert_header.py | 2 +- 4 files changed, 7 insertions(+), 2 deletions(-) diff --git a/libavfilter/dnn/dnn_backend_native_layer_mathunary.c b/libavfilter/dnn/dnn_backend_native_layer_mathunary.c index b77b84a794..c83d50db64 100644 --- a/libavfilter/dnn/dnn_backend_native_layer_mathunary.c +++ b/libavfilter/dnn/dnn_backend_native_layer_mathunary.c @@ -124,6 +124,10 @@ int dnn_execute_layer_math_unary(DnnOperand *operands, const int32_t *input_oper for (int i = 0; i < dims_count; ++i) dst[i] = acosh(src[i]); return 0; + case DMUO_ATANH: + for (int i = 0; i < dims_count; ++i) + dst[i] = atanh(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 index eb30231549..8076356ba4 100644 --- a/libavfilter/dnn/dnn_backend_native_layer_mathunary.h +++ b/libavfilter/dnn/dnn_backend_native_layer_mathunary.h @@ -42,6 +42,7 @@ typedef enum { DMUO_TANH = 9, DMUO_ASINH = 10, DMUO_ACOSH = 11, + DMUO_ATANH = 12, DMUO_COUNT } DNNMathUnaryOperation; diff --git a/tools/python/convert_from_tensorflow.py b/tools/python/convert_from_tensorflow.py index 1e73e3aefe..85db7bf710 100644 --- a/tools/python/convert_from_tensorflow.py +++ b/tools/python/convert_from_tensorflow.py @@ -72,7 +72,7 @@ class TFConverter: self.conv2d_scopename_inputname_dict = {} 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, 'Sin':1, 'Cos':2, 'Tan':3, 'Asin':4, 'Acos':5, 'Atan':6, 'Sinh':7, 'Cosh':8, 'Tanh':9, 'Asinh':10, 'Acosh':11} + self.mathun2code = {'Abs':0, 'Sin':1, 'Cos':2, 'Tan':3, 'Asin':4, 'Acos':5, 'Atan':6, 'Sinh':7, 'Cosh':8, 'Tanh':9, 'Asinh':10, 'Acosh':11, 'Atanh':12} self.mirrorpad_mode = {'CONSTANT':0, 'REFLECT':1, 'SYMMETRIC':2} self.name_operand_dict = {} diff --git a/tools/python/convert_header.py b/tools/python/convert_header.py index 8fc3438552..9851d84144 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 = 17 +minor = 18