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Posted to commits@tvm.apache.org by GitBox <gi...@apache.org> on 2020/06/04 04:38:06 UTC
[GitHub] [incubator-tvm] yongwww commented on a change in pull request #5699: [Frontend][TensorFlow] Improve Control Flow and TensorArray
yongwww commented on a change in pull request #5699:
URL: https://github.com/apache/incubator-tvm/pull/5699#discussion_r434980636
##########
File path: tests/python/frontend/tensorflow/test_forward.py
##########
@@ -2238,6 +2258,40 @@ def test_forward_resnetv2():
tvm.testing.assert_allclose(np.squeeze(tvm_output[0]), np.squeeze(tf_output[0]),
rtol=1e-5, atol=1e-5)
+#######################################################################
+# SSD
+# ---
+
+
+def test_forward_ssd():
+ '''test resnet model'''
Review comment:
```suggestion
'''test SSD with backbone MobileNet V1'''
```
##########
File path: tests/python/frontend/tensorflow/test_forward.py
##########
@@ -2238,6 +2258,40 @@ def test_forward_resnetv2():
tvm.testing.assert_allclose(np.squeeze(tvm_output[0]), np.squeeze(tf_output[0]),
rtol=1e-5, atol=1e-5)
+#######################################################################
+# SSD
+# ---
+
+
+def test_forward_ssd():
+ '''test resnet model'''
+ if is_gpu_available():
+ with tf.Graph().as_default():
+ graph_def = tf_testing.get_workload(
+ "object_detection/ssd_mobilenet_v1_ppn_shared_"
+ "box_predictor_300x300_coco14_sync_2018_07_03.pb")
+ # Call the utility to import the graph definition into default graph.
+ graph_def = tf_testing.ProcessGraphDefParam(graph_def)
+
+ data = np.random.uniform(0.0, 255.0, size=(1, 512, 512, 3)).astype('float32')
+ in_node = "image_tensor"
+ out_node = ['detection_boxes', "detection_scores", "detection_classes"]
+
+ with tf.Session() as sess:
+ tf_output = run_tf_graph(
+ sess, data, '{}:0'.format(in_node), ["{}:0".format(oname) for oname in out_node])
+ # TODO(kevinthesun): enable gpu test when VM heterogeneous execution is ready.
+ for device in ["llvm"]:
+ ctx = tvm.context(device, 0)
+ if not ctx.exist:
+ print("Skip because %s is not enabled" % device)
+ continue
+ tvm_output = run_tvm_graph(graph_def, data, in_node, len(out_node),
+ target=device, layout="NCHW", mode="vm")
+ for i in range(len(out_node)):
+ tvm.testing.assert_allclose(tvm_output[i], tf_output[i],
+ rtol=1e-3, atol=1e-3)
Review comment:
```suggestion
def _test_forward_ssd(model_url, in_node, out_nodes, in_shape):
graph_def = tf_testing.get_workload(model_url)
# Call the utility to import the graph definition into default graph.
graph_def = tf_testing.ProcessGraphDefParam(graph_def)
data = np.random.uniform(0.0, 255.0, size=in_shape).astype('float32')
with tf.Session() as sess:
tf_output = run_tf_graph(
sess, data, '{}:0'.format(in_node), ["{}:0".format(oname) for oname in out_nodes])
# TODO(kevinthesun): enable gpu test when VM heterogeneous execution is ready.
for device in ["llvm"]:
ctx = tvm.context(device, 0)
if not ctx.exist:
print("Skip because %s is not enabled" % device)
continue
tvm_output = run_tvm_graph(graph_def, data, in_node, len(out_nodes),
target=device, layout="NCHW", mode="vm")
for i in range(len(out_nodes)):
tvm.testing.assert_allclose(tvm_output[i], tf_output[i],
rtol=1e-3, atol=1e-3)
_test_forward_ssd("object_detection/ssd_mobilenet_v1_ppn_shared_"
"box_predictor_300x300_coco14_sync_2018_07_03.pb",
"image_tensor",
['detection_boxes', "detection_scores", "detection_classes"],
(1, 512, 512, 3))
```
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