[FFmpeg-cvslog] fate: add unit test for dnn-layer-pad
Guo, Yejun
git at videolan.org
Mon Jul 29 18:35:11 EEST 2019
ffmpeg | branch: master | Guo, Yejun <yejun.guo at intel.com> | Mon Jul 29 09:56:40 2019 +0800| [3805aae47966b691f825abab6843f55676437a02] | committer: Pedro Arthur
fate: add unit test for dnn-layer-pad
'make fate-dnn-layer-pad' to run the test
Signed-off-by: Guo, Yejun <yejun.guo at intel.com>
Signed-off-by: Pedro Arthur <bygrandao at gmail.com>
> http://git.videolan.org/gitweb.cgi/ffmpeg.git/?a=commit;h=3805aae47966b691f825abab6843f55676437a02
---
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(-)
diff --git a/tests/Makefile b/tests/Makefile
index 624292d451..0ef571b067 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 0000000000..b2e668003f
--- /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 0000000000..28a49eb55a
--- /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 0000000000..a077a4a11e
--- /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)
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