LGTM.
Pushed, thanks!
Em dom, 28 de jul de 2019 às 22:59, Guo, Yejun <yejun....@intel.com> escreveu:
>
> 'make fate-dnn-layer-pad' to run the test
>
> Signed-off-by: Guo, Yejun <yejun....@intel.com>
> ---
> tests/Makefile | 5 +-
> tests/dnn/Makefile | 11 +++
> tests/dnn/dnn-layer-pad-test.c | 203
> +++++++++++++++++++++++++++++++++++++++++
> tests/fate/dnn.mak | 8 ++
> 4 files changed, 226 insertions(+), 1 deletion(-)
> create mode 100644 tests/dnn/Makefile
> create mode 100644 tests/dnn/dnn-layer-pad-test.c
> create mode 100644 tests/fate/dnn.mak
>
> diff --git a/tests/Makefile b/tests/Makefile
> index 624292d..0ef571b 100644
> --- a/tests/Makefile
> +++ b/tests/Makefile
> @@ -10,7 +10,8 @@ FFMPEG=ffmpeg$(PROGSSUF)$(EXESUF)
> $(AREF): CMP=
>
> APITESTSDIR := tests/api
> -FATE_OUTDIRS = tests/data tests/data/fate tests/data/filtergraphs
> tests/data/lavf tests/data/lavf-fate tests/data/pixfmt tests/vsynth1
> $(APITESTSDIR)
> +DNNTESTSDIR := tests/dnn
> +FATE_OUTDIRS = tests/data tests/data/fate tests/data/filtergraphs
> tests/data/lavf tests/data/lavf-fate tests/data/pixfmt tests/vsynth1
> $(APITESTSDIR) $(DNNTESTSDIR)
> OUTDIRS += $(FATE_OUTDIRS)
>
> $(VREF): tests/videogen$(HOSTEXESUF) | tests/vsynth1
> @@ -85,6 +86,7 @@ FILTERDEMDECENCMUX = $(call ALLYES, $(1:%=%_FILTER)
> $(2)_DEMUXER $(3)_DECODER $(
> PARSERDEMDEC = $(call ALLYES, $(1)_PARSER $(2)_DEMUXER $(3)_DECODER)
>
> include $(SRC_PATH)/$(APITESTSDIR)/Makefile
> +include $(SRC_PATH)/$(DNNTESTSDIR)/Makefile
>
> include $(SRC_PATH)/tests/fate/acodec.mak
> include $(SRC_PATH)/tests/fate/vcodec.mak
> @@ -118,6 +120,7 @@ include $(SRC_PATH)/tests/fate/cover-art.mak
> include $(SRC_PATH)/tests/fate/dca.mak
> include $(SRC_PATH)/tests/fate/demux.mak
> include $(SRC_PATH)/tests/fate/dfa.mak
> +include $(SRC_PATH)/tests/fate/dnn.mak
> include $(SRC_PATH)/tests/fate/dnxhd.mak
> include $(SRC_PATH)/tests/fate/dpcm.mak
> include $(SRC_PATH)/tests/fate/ea.mak
> diff --git a/tests/dnn/Makefile b/tests/dnn/Makefile
> new file mode 100644
> index 0000000..b2e6680
> --- /dev/null
> +++ b/tests/dnn/Makefile
> @@ -0,0 +1,11 @@
> +DNNTESTPROGS += dnn-layer-pad
> +
> +DNNTESTOBJS := $(DNNTESTOBJS:%=$(DNNTESTSDIR)%)
> $(DNNTESTPROGS:%=$(DNNTESTSDIR)/%-test.o)
> +DNNTESTPROGS := $(DNNTESTPROGS:%=$(DNNTESTSDIR)/%-test$(EXESUF))
> +-include $(wildcard $(DNNTESTOBJS:.o=.d))
> +
> +$(DNNTESTPROGS): %$(EXESUF): %.o $(FF_DEP_LIBS)
> + $(LD) $(LDFLAGS) $(LDEXEFLAGS) $(LD_O) $(filter %.o,$^)
> $(FF_EXTRALIBS) $(ELIBS)
> +
> +testclean::
> + $(RM) $(addprefix $(DNNTESTSDIR)/,$(CLEANSUFFIXES) *-test$(EXESUF))
> diff --git a/tests/dnn/dnn-layer-pad-test.c b/tests/dnn/dnn-layer-pad-test.c
> new file mode 100644
> index 0000000..28a49eb
> --- /dev/null
> +++ b/tests/dnn/dnn-layer-pad-test.c
> @@ -0,0 +1,203 @@
> +/*
> + * Copyright (c) 2019 Guo Yejun
> + *
> + * 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
> + */
> +
> +#include <stdio.h>
> +#include <string.h>
> +#include <math.h>
> +#include "libavfilter/dnn/dnn_backend_native_layer_pad.h"
> +
> +#define EPSON 0.00001
> +
> +static int test_with_mode_symmetric(void)
> +{
> + // the input data and expected data are generated with below python code.
> + /*
> + x = tf.placeholder(tf.float32, shape=[1, None, None, 3])
> + y = tf.pad(x, [[0, 0], [2, 3], [3, 2], [0, 0]], 'SYMMETRIC')
> + data = np.arange(48).reshape(1, 4, 4, 3);
> +
> + sess=tf.Session()
> + sess.run(tf.global_variables_initializer())
> + output = sess.run(y, feed_dict={x: data})
> +
> + print(list(data.flatten()))
> + print(list(output.flatten()))
> + print(data.shape)
> + print(output.shape)
> + */
> +
> + LayerPadParams params;
> + float input[1*4*4*3] = {
> + 0, 1, 2, 3, 4, 5, 6, 7, 8, 9, 10, 11, 12, 13, 14, 15, 16, 17, 18,
> 19, 20, 21, 22, 23, 24, 25, 26, 27, 28, 29, 30, 31, 32, 33, 34, 35, 36, 37,
> 38, 39, 40, 41, 42, 43, 44, 45, 46, 47
> + };
> + float expected_output[1*9*9*3] = {
> + 18.0, 19.0, 20.0, 15.0, 16.0, 17.0, 12.0, 13.0, 14.0, 12.0, 13.0,
> 14.0, 15.0, 16.0, 17.0, 18.0, 19.0, 20.0, 21.0, 22.0, 23.0, 21.0, 22.0, 23.0,
> 18.0, 19.0, 20.0, 6.0, 7.0, 8.0, 3.0,
> + 4.0, 5.0, 0.0, 1.0, 2.0, 0.0, 1.0, 2.0, 3.0, 4.0, 5.0, 6.0, 7.0,
> 8.0, 9.0, 10.0, 11.0, 9.0, 10.0, 11.0, 6.0, 7.0, 8.0, 6.0, 7.0, 8.0, 3.0,
> 4.0, 5.0, 0.0, 1.0, 2.0, 0.0, 1.0, 2.0, 3.0,
> + 4.0, 5.0, 6.0, 7.0, 8.0, 9.0, 10.0, 11.0, 9.0, 10.0, 11.0, 6.0, 7.0,
> 8.0, 18.0, 19.0, 20.0, 15.0, 16.0, 17.0, 12.0, 13.0, 14.0, 12.0, 13.0, 14.0,
> 15.0, 16.0, 17.0, 18.0, 19.0, 20.0,
> + 21.0, 22.0, 23.0, 21.0, 22.0, 23.0, 18.0, 19.0, 20.0, 30.0, 31.0,
> 32.0, 27.0, 28.0, 29.0, 24.0, 25.0, 26.0, 24.0, 25.0, 26.0, 27.0, 28.0, 29.0,
> 30.0, 31.0, 32.0, 33.0, 34.0, 35.0, 33.0,
> + 34.0, 35.0, 30.0, 31.0, 32.0, 42.0, 43.0, 44.0, 39.0, 40.0, 41.0,
> 36.0, 37.0, 38.0, 36.0, 37.0, 38.0, 39.0, 40.0, 41.0, 42.0, 43.0, 44.0, 45.0,
> 46.0, 47.0, 45.0, 46.0, 47.0, 42.0, 43.0,
> + 44.0, 42.0, 43.0, 44.0, 39.0, 40.0, 41.0, 36.0, 37.0, 38.0, 36.0,
> 37.0, 38.0, 39.0, 40.0, 41.0, 42.0, 43.0, 44.0, 45.0, 46.0, 47.0, 45.0, 46.0,
> 47.0, 42.0, 43.0, 44.0, 30.0, 31.0, 32.0,
> + 27.0, 28.0, 29.0, 24.0, 25.0, 26.0, 24.0, 25.0, 26.0, 27.0, 28.0,
> 29.0, 30.0, 31.0, 32.0, 33.0, 34.0, 35.0, 33.0, 34.0, 35.0, 30.0, 31.0, 32.0,
> 18.0, 19.0, 20.0, 15.0, 16.0, 17.0, 12.0,
> + 13.0, 14.0, 12.0, 13.0, 14.0, 15.0, 16.0, 17.0, 18.0, 19.0, 20.0,
> 21.0, 22.0, 23.0, 21.0, 22.0, 23.0, 18.0, 19.0, 20.0
> + };
> + float output[1*9*9*3];
> + memset(output, 0, sizeof(output));
> +
> + params.mode = LPMP_SYMMETRIC;
> + params.paddings[0][0] = 0;
> + params.paddings[0][1] = 0;
> + params.paddings[1][0] = 2;
> + params.paddings[1][1] = 3;
> + params.paddings[2][0] = 3;
> + params.paddings[2][1] = 2;
> + params.paddings[3][0] = 0;
> + params.paddings[3][1] = 0;
> +
> + dnn_execute_layer_pad(input, output, ¶ms, 1, 4, 4, 3);
> +
> + for (int i = 0; i < sizeof(output) / sizeof(float); i++) {
> + if (fabs(output[i] - expected_output[i]) > EPSON) {
> + printf("at index %d, output: %f, expected_output: %f\n", i,
> output[i], expected_output[i]);
> + return 1;
> + }
> + }
> +
> + return 0;
> +
> +}
> +
> +static int test_with_mode_reflect(void)
> +{
> + // the input data and expected data are generated with below python code.
> + /*
> + x = tf.placeholder(tf.float32, shape=[3, None, None, 3])
> + y = tf.pad(x, [[1, 2], [0, 0], [0, 0], [0, 0]], 'REFLECT')
> + data = np.arange(36).reshape(3, 2, 2, 3);
> +
> + sess=tf.Session()
> + sess.run(tf.global_variables_initializer())
> + output = sess.run(y, feed_dict={x: data})
> +
> + print(list(data.flatten()))
> + print(list(output.flatten()))
> + print(data.shape)
> + print(output.shape)
> + */
> +
> + LayerPadParams params;
> + float input[3*2*2*3] = {
> + 0, 1, 2, 3, 4, 5, 6, 7, 8, 9, 10, 11, 12, 13, 14, 15, 16, 17, 18,
> 19, 20, 21, 22, 23, 24, 25, 26, 27, 28, 29, 30, 31, 32, 33, 34, 35
> + };
> + float expected_output[6*2*2*3] = {
> + 12.0, 13.0, 14.0, 15.0, 16.0, 17.0, 18.0, 19.0, 20.0, 21.0, 22.0,
> 23.0, 0.0, 1.0, 2.0, 3.0, 4.0, 5.0, 6.0, 7.0, 8.0, 9.0, 10.0, 11.0,
> + 12.0, 13.0, 14.0, 15.0, 16.0, 17.0, 18.0, 19.0, 20.0, 21.0, 22.0,
> 23.0, 24.0, 25.0, 26.0, 27.0, 28.0, 29.0, 30.0, 31.0, 32.0, 33.0, 34.0,
> + 35.0, 12.0, 13.0, 14.0, 15.0, 16.0, 17.0, 18.0, 19.0, 20.0, 21.0,
> 22.0, 23.0, 0.0, 1.0, 2.0, 3.0, 4.0, 5.0, 6.0, 7.0, 8.0, 9.0, 10.0, 11.0
> + };
> + float output[6*2*2*3];
> + memset(output, 0, sizeof(output));
> +
> + params.mode = LPMP_REFLECT;
> + params.paddings[0][0] = 1;
> + params.paddings[0][1] = 2;
> + params.paddings[1][0] = 0;
> + params.paddings[1][1] = 0;
> + params.paddings[2][0] = 0;
> + params.paddings[2][1] = 0;
> + params.paddings[3][0] = 0;
> + params.paddings[3][1] = 0;
> +
> + dnn_execute_layer_pad(input, output, ¶ms, 3, 2, 2, 3);
> +
> + for (int i = 0; i < sizeof(output) / sizeof(float); i++) {
> + if (fabs(output[i] - expected_output[i]) > EPSON) {
> + printf("at index %d, output: %f, expected_output: %f\n", i,
> output[i], expected_output[i]);
> + return 1;
> + }
> + }
> +
> + return 0;
> +
> +}
> +
> +static int test_with_mode_constant(void)
> +{
> + // the input data and expected data are generated with below python code.
> + /*
> + x = tf.placeholder(tf.float32, shape=[1, None, None, 3])
> + y = tf.pad(x, [[0, 0], [1, 0], [0, 0], [1, 2]], 'CONSTANT',
> constant_values=728)
> + data = np.arange(12).reshape(1, 2, 2, 3);
> +
> + sess=tf.Session()
> + sess.run(tf.global_variables_initializer())
> + output = sess.run(y, feed_dict={x: data})
> +
> + print(list(data.flatten()))
> + print(list(output.flatten()))
> + print(data.shape)
> + print(output.shape)
> + */
> +
> + LayerPadParams params;
> + float input[1*2*2*3] = {
> + 0, 1, 2, 3, 4, 5, 6, 7, 8, 9, 10, 11
> + };
> + float expected_output[1*3*2*6] = {
> + 728.0, 728.0, 728.0, 728.0, 728.0, 728.0, 728.0, 728.0, 728.0,
> 728.0, 728.0,
> + 728.0, 728.0, 0.0, 1.0, 2.0, 728.0, 728.0, 728.0, 3.0, 4.0, 5.0,
> 728.0, 728.0,
> + 728.0, 6.0, 7.0, 8.0, 728.0, 728.0, 728.0, 9.0, 10.0, 11.0, 728.0,
> 728.0
> + };
> + float output[1*3*2*6];
> + memset(output, 0, sizeof(output));
> +
> + params.mode = LPMP_CONSTANT;
> + params.constant_values = 728;
> + params.paddings[0][0] = 0;
> + params.paddings[0][1] = 0;
> + params.paddings[1][0] = 1;
> + params.paddings[1][1] = 0;
> + params.paddings[2][0] = 0;
> + params.paddings[2][1] = 0;
> + params.paddings[3][0] = 1;
> + params.paddings[3][1] = 2;
> +
> + dnn_execute_layer_pad(input, output, ¶ms, 1, 2, 2, 3);
> +
> + for (int i = 0; i < sizeof(output) / sizeof(float); i++) {
> + if (fabs(output[i] - expected_output[i]) > EPSON) {
> + printf("at index %d, output: %f, expected_output: %f\n", i,
> output[i], expected_output[i]);
> + return 1;
> + }
> + }
> +
> + return 0;
> +
> +}
> +
> +int main(int argc, char **argv)
> +{
> + if (test_with_mode_symmetric())
> + return 1;
> +
> + if (test_with_mode_reflect())
> + return 1;
> +
> + if (test_with_mode_constant())
> + return 1;
> +}
> diff --git a/tests/fate/dnn.mak b/tests/fate/dnn.mak
> new file mode 100644
> index 0000000..a077a4a
> --- /dev/null
> +++ b/tests/fate/dnn.mak
> @@ -0,0 +1,8 @@
> +FATE_DNN += fate-dnn-layer-pad
> +fate-dnn-layer-pad: $(DNNTESTSDIR)/dnn-layer-pad-test$(EXESUF)
> +fate-dnn-layer-pad: CMD = run $(DNNTESTSDIR)/dnn-layer-pad-test$(EXESUF)
> +fate-dnn-layer-pad: CMP = null
> +
> +FATE-yes += $(FATE_DNN)
> +
> +fate-dnn: $(FATE_DNN)
> --
> 2.7.4
>
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