From 373a8caa79293bcfb9a026fa73e9f25885240dd0 Mon Sep 17 00:00:00 2001
From: Siva <sivar.b@huawei.com>
Date: Tue, 26 Jun 2018 22:45:24 +0530
Subject: [PATCH] [NNVM][TENSORFLOW] Mobilenet support. (#1335)
---
nnvm/python/nnvm/frontend/tensorflow.py | 52 +++++++++-----
nnvm/python/nnvm/testing/tf.py | 70 +++++++++++++------
.../frontend/tensorflow/test_forward.py | 24 +++++++
3 files changed, 109 insertions(+), 37 deletions(-)
diff --git a/nnvm/python/nnvm/frontend/tensorflow.py b/nnvm/python/nnvm/frontend/tensorflow.py
index 3ab997617..715365178 100644
--- a/nnvm/python/nnvm/frontend/tensorflow.py
+++ b/nnvm/python/nnvm/frontend/tensorflow.py
@@ -35,6 +35,11 @@ class AttrCvt(object):
self._ignores.append('use_cudnn_on_gpu')
self._ignores.append('_node_name')
self._ignores.append('is_training')
+ # Retain the names
+ try:
+ attrs['name'] = attrs['_node_name']
+ except KeyError:
+ pass
return AttrConvert(self._op_name, self._transforms, self._excludes,
self._disables, self._ignores, self._extras,
self._custom_check)(inputs, attrs, *args)
@@ -405,13 +410,19 @@ def _concat():
def _reshape():
def _impl(inputs, attr, params):
- pop_node = inputs.pop(1)
- shape_arg = params[pop_node.list_output_names()[0]]
- params.pop(pop_node.list_output_names()[0])
- return AttrCvt(
- op_name="reshape",
- extras={'shape':tuple(shape_arg.asnumpy())},
- ignores=['Tshape'])(inputs, attr)
+ try:
+ pop_node = inputs[1]
+ shape_arg = params.pop(pop_node.list_output_names()[0])
+ inputs.pop(1)
+
+ return AttrCvt(
+ op_name="reshape",
+ extras={'shape':tuple(shape_arg.asnumpy())},
+ ignores=['Tshape'])(inputs, attr)
+ except KeyError:
+ return AttrCvt(
+ op_name="reshape_like",
+ ignores=['Tshape'])(inputs, attr)
return _impl
def _bias_add():
@@ -427,6 +438,18 @@ def _squeeze():
ignores=['T'])(inputs, attr)
return _impl
+def _fused_batch_norm():
+ def _impl(inputs, attr, params):
+ # Tensorflow: (data, gamma, beta, moving_mean, moving_variance)
+ # NNVM: (data, gamma, beta, moving_mean, moving_varience)
+ return AttrCvt(
+ op_name='batch_norm',
+ transforms={'scale_after_normalization':'scale', 'variance_epsilon':'epsilon'},
+ extras={'axis': 3}, # Fix axis
+ ignores=['data_format'],
+ disables=['momentum'])(inputs, attr)
+ return _impl
+
def _batch_norm():
def _impl(inputs, attr, params):
# Rearrange inputs from
@@ -445,19 +468,14 @@ def _batch_norm():
def _relu6():
def _impl(inputs, attr, params):
- return _sym.clip(inputs[0], a_min=0, a_max=6)
+ return _sym.clip(inputs[0], a_min=0, a_max=6, name=attr['_node_name'])
return _impl
def _shape():
def _impl(inputs, attr, params):
- input_shapes = attr['_input_shapes'][inputs[0]]
-
- # Fix the -1 dimensions to 1
- input_shapes[0] = [1 if x == -1 else x for x in input_shapes[0]]
- params[attr['_node_name']] = tvm.nd.array(input_shapes[0])
-
- return _sym.Variable(name=attr['_node_name'],
- shape=params[attr['_node_name']].shape)
+ # Result of this operator is prominently used by reshape operator.
+ # Just pass the input as it is so that reshape_like can be used there.
+ return inputs[0]
return _impl
# compatible operators that do NOT require any conversion.
@@ -491,7 +509,7 @@ _convert_map = {
'Add' : _elemwise('add'),
'Rsqrt' : _rsqrt(),
'Squeeze' : _squeeze(),
- 'FusedBatchNorm' : _batch_norm(),
+ 'FusedBatchNorm' : _fused_batch_norm(),
'Relu6' : _relu6(),
'DepthwiseConv2dNative' : _depthwise_conv(),
'Shape' : _shape(),
diff --git a/nnvm/python/nnvm/testing/tf.py b/nnvm/python/nnvm/testing/tf.py
index 3421573e3..1762ce565 100644
--- a/nnvm/python/nnvm/testing/tf.py
+++ b/nnvm/python/nnvm/testing/tf.py
@@ -153,6 +153,35 @@ def read_normalized_tensor_from_image_file(file_name,
np_array = normalized.eval()
return np_array
+def get_workload(model_path):
+ """ Import workload from frozen protobuf
+
+ Parameters
+ ----------
+ model_path: str
+ model_path on remote repository to download from.
+
+ Returns
+ -------
+ graph_def: graphdef
+ graph_def is the tensorflow workload for mobilenet.
+
+ """
+
+ repo_base = 'https://github.com/dmlc/web-data/raw/master/tensorflow/models/'
+ model_name = os.path.basename(model_path)
+ model_url = os.path.join(repo_base, model_path)
+
+ from mxnet.gluon.utils import download
+ download(model_url, model_name)
+
+ # Creates graph from saved graph_def.pb.
+ with tf.gfile.FastGFile(os.path.join("./", model_name), 'rb') as f:
+ graph_def = tf.GraphDef()
+ graph_def.ParseFromString(f.read())
+ graph = tf.import_graph_def(graph_def, name='')
+ return graph_def
+
def get_workload_inception_v3():
""" Import Inception V3 workload from frozen protobuf
@@ -168,23 +197,15 @@ def get_workload_inception_v3():
"""
repo_base = 'https://github.com/dmlc/web-data/raw/master/tensorflow/models/InceptionV3/'
- model_name = 'inception_v3_2016_08_28_frozen-with_shapes.pb'
- model_url = os.path.join(repo_base, model_name)
+ model_path = 'InceptionV3/inception_v3_2016_08_28_frozen-with_shapes.pb'
+
image_name = 'elephant-299.jpg'
image_url = os.path.join(repo_base, image_name)
-
from mxnet.gluon.utils import download
- download(model_url, model_name)
download(image_url, image_name)
-
normalized = read_normalized_tensor_from_image_file(os.path.join("./", image_name))
- # Creates graph from saved graph_def.pb.
- with tf.gfile.FastGFile(os.path.join("./", model_name), 'rb') as f:
- graph_def = tf.GraphDef()
- graph_def.ParseFromString(f.read())
- graph = tf.import_graph_def(graph_def, name='')
- return (normalized, graph_def)
+ return (normalized, get_workload(model_path))
def get_workload_inception_v1():
""" Import Inception V1 workload from frozen protobuf
@@ -203,13 +224,11 @@ def get_workload_inception_v1():
"""
repo_base = 'https://github.com/dmlc/web-data/raw/master/tensorflow/models/InceptionV1/'
- model_name = 'classify_image_graph_def-with_shapes.pb'
- model_url = os.path.join(repo_base, model_name)
+ model_path = 'InceptionV1/classify_image_graph_def-with_shapes.pb'
image_name = 'elephant-299.jpg'
image_url = os.path.join(repo_base, image_name)
from mxnet.gluon.utils import download
- download(model_url, model_name)
download(image_url, image_name)
if not tf.gfile.Exists(os.path.join("./", image_name)):
@@ -221,9 +240,20 @@ def get_workload_inception_v1():
tvm_data = Image.open(os.path.join("./", image_name)).resize((299, 299))
tvm_data = np.array(tvm_data)
- # Creates graph from saved graph_def.pb.
- with tf.gfile.FastGFile(os.path.join("./", model_name), 'rb') as f:
- graph_def = tf.GraphDef()
- graph_def.ParseFromString(f.read())
- graph = tf.import_graph_def(graph_def, name='')
- return (image_data, tvm_data, graph_def)
+ return (image_data, tvm_data, get_workload(model_path))
+
+def get_workload_mobilenet():
+ """ Import mobilenet workload from frozen protobuf
+
+ Parameters
+ ----------
+ Nothing.
+
+ Returns
+ -------
+ graph_def: graphdef
+ graph_def is the tensorflow workload for mobilenet.
+
+ """
+
+ return get_workload("MobilenetV1/mobilenet_v1_1.0_224_frozen-with-shapes.pb")
diff --git a/nnvm/tests/python/frontend/tensorflow/test_forward.py b/nnvm/tests/python/frontend/tensorflow/test_forward.py
index 4e742a4a5..6dc8cfab2 100644
--- a/nnvm/tests/python/frontend/tensorflow/test_forward.py
+++ b/nnvm/tests/python/frontend/tensorflow/test_forward.py
@@ -406,6 +406,29 @@ def test_forward_inception_v1():
np.testing.assert_allclose(tf_output, tvm_output, rtol=2e-2, atol=2e-2)
+#######################################################################
+# Mobilenet
+# ---------
+def test_forward_mobilenet():
+ '''test mobilenet model'''
+ with tf.Graph().as_default():
+ graph_def = nnvm.testing.tf.get_workload_mobilenet()
+ # Call the utility to import the graph definition into default graph.
+ graph_def = nnvm.testing.tf.ProcessGraphDefParam(graph_def)
+
+ data = np.random.uniform(size=(1, 224, 224, 3)).astype('float32')
+ out_node = 'MobilenetV1/Predictions/Reshape_1'
+
+ with tf.Session() as sess:
+ tf_output = run_tf_graph(sess, data, 'input:0', out_node + ':0')
+
+ out_shape = tf_output.shape
+ tvm_output = run_tvm_graph(graph_def, data, 'input', out_shape, 'float32')
+ top_tvm = np.squeeze(tvm_output).argsort()[-10:][::-1]
+ top_tf = np.squeeze(tf_output).argsort()[-10:][::-1]
+
+ np.testing.assert_allclose(np.squeeze(tvm_output), np.squeeze(tf_output), rtol=1e-5, atol=1e-5)
+
#######################################################################
# Main
# ----
@@ -419,3 +442,4 @@ if __name__ == '__main__':
test_forward_multi_input()
test_forward_inception_v3()
test_forward_inception_v1()
+ test_forward_mobilenet()
--
GitLab