Python nets.inception.inception_v4_base() Examples

The following are 30 code examples of nets.inception.inception_v4_base(). You can vote up the ones you like or vote down the ones you don't like, and go to the original project or source file by following the links above each example. You may also want to check out all available functions/classes of the module nets.inception , or try the search function .
Example #1
Source File: inception_v4_test.py    From TwinGAN with Apache License 2.0 6 votes vote down vote up 
def testBuildOnlyUpToFinalEndpoint(self):
    batch_size = 5
    height, width = 299, 299
    all_endpoints = [
        'Conv2d_1a_3x3', 'Conv2d_2a_3x3', 'Conv2d_2b_3x3', 'Mixed_3a',
        'Mixed_4a', 'Mixed_5a', 'Mixed_5b', 'Mixed_5c', 'Mixed_5d',
        'Mixed_5e', 'Mixed_6a', 'Mixed_6b', 'Mixed_6c', 'Mixed_6d',
        'Mixed_6e', 'Mixed_6f', 'Mixed_6g', 'Mixed_6h', 'Mixed_7a',
        'Mixed_7b', 'Mixed_7c', 'Mixed_7d']
    for index, endpoint in enumerate(all_endpoints):
      with tf.Graph().as_default():
        inputs = tf.random_uniform((batch_size, height, width, 3))
        out_tensor, end_points = inception.inception_v4_base(
            inputs, final_endpoint=endpoint)
        self.assertTrue(out_tensor.op.name.startswith(
            'InceptionV4/' + endpoint))
        self.assertItemsEqual(all_endpoints[:index+1], end_points)
Example #2
Source File: inception_v4_test.py    From object_detection_with_tensorflow with MIT License 6 votes vote down vote up 
def testBuildBaseNetwork(self):
    batch_size = 5
    height, width = 299, 299
    inputs = tf.random_uniform((batch_size, height, width, 3))
    net, end_points = inception.inception_v4_base(inputs)
    self.assertTrue(net.op.name.startswith(
        'InceptionV4/Mixed_7d'))
    self.assertListEqual(net.get_shape().as_list(), [batch_size, 8, 8, 1536])
    expected_endpoints = [
        'Conv2d_1a_3x3', 'Conv2d_2a_3x3', 'Conv2d_2b_3x3', 'Mixed_3a',
        'Mixed_4a', 'Mixed_5a', 'Mixed_5b', 'Mixed_5c', 'Mixed_5d',
        'Mixed_5e', 'Mixed_6a', 'Mixed_6b', 'Mixed_6c', 'Mixed_6d',
        'Mixed_6e', 'Mixed_6f', 'Mixed_6g', 'Mixed_6h', 'Mixed_7a',
        'Mixed_7b', 'Mixed_7c', 'Mixed_7d']
    self.assertItemsEqual(end_points.keys(), expected_endpoints)
    for name, op in end_points.iteritems():
      self.assertTrue(op.name.startswith('InceptionV4/' + name))
Example #3
Source File: inception_v4_test.py    From object_detection_kitti with Apache License 2.0 6 votes vote down vote up 
def testBuildBaseNetwork(self):
    batch_size = 5
    height, width = 299, 299
    inputs = tf.random_uniform((batch_size, height, width, 3))
    net, end_points = inception.inception_v4_base(inputs)
    self.assertTrue(net.op.name.startswith(
        'InceptionV4/Mixed_7d'))
    self.assertListEqual(net.get_shape().as_list(), [batch_size, 8, 8, 1536])
    expected_endpoints = [
        'Conv2d_1a_3x3', 'Conv2d_2a_3x3', 'Conv2d_2b_3x3', 'Mixed_3a',
        'Mixed_4a', 'Mixed_5a', 'Mixed_5b', 'Mixed_5c', 'Mixed_5d',
        'Mixed_5e', 'Mixed_6a', 'Mixed_6b', 'Mixed_6c', 'Mixed_6d',
        'Mixed_6e', 'Mixed_6f', 'Mixed_6g', 'Mixed_6h', 'Mixed_7a',
        'Mixed_7b', 'Mixed_7c', 'Mixed_7d']
    self.assertItemsEqual(end_points.keys(), expected_endpoints)
    for name, op in end_points.iteritems():
      self.assertTrue(op.name.startswith('InceptionV4/' + name))
Example #4
Source File: inception_v4_test.py    From SENet-tensorflow-slim with MIT License 6 votes vote down vote up 
def testBuildBaseNetwork(self):
    batch_size = 5
    height, width = 299, 299
    inputs = tf.random_uniform((batch_size, height, width, 3))
    net, end_points = inception.inception_v4_base(inputs)
    self.assertTrue(net.op.name.startswith(
        'InceptionV4/Mixed_7d'))
    self.assertListEqual(net.get_shape().as_list(), [batch_size, 8, 8, 1536])
    expected_endpoints = [
        'Conv2d_1a_3x3', 'Conv2d_2a_3x3', 'Conv2d_2b_3x3', 'Mixed_3a',
        'Mixed_4a', 'Mixed_5a', 'Mixed_5b', 'Mixed_5c', 'Mixed_5d',
        'Mixed_5e', 'Mixed_6a', 'Mixed_6b', 'Mixed_6c', 'Mixed_6d',
        'Mixed_6e', 'Mixed_6f', 'Mixed_6g', 'Mixed_6h', 'Mixed_7a',
        'Mixed_7b', 'Mixed_7c', 'Mixed_7d']
    self.assertItemsEqual(end_points.keys(), expected_endpoints)
    for name, op in end_points.items():
      self.assertTrue(op.name.startswith('InceptionV4/' + name))
Example #5
Source File: inception_v4_test.py    From SENet-tensorflow-slim with MIT License 6 votes vote down vote up 
def testBuildOnlyUpToFinalEndpoint(self):
    batch_size = 5
    height, width = 299, 299
    all_endpoints = [
        'Conv2d_1a_3x3', 'Conv2d_2a_3x3', 'Conv2d_2b_3x3', 'Mixed_3a',
        'Mixed_4a', 'Mixed_5a', 'Mixed_5b', 'Mixed_5c', 'Mixed_5d',
        'Mixed_5e', 'Mixed_6a', 'Mixed_6b', 'Mixed_6c', 'Mixed_6d',
        'Mixed_6e', 'Mixed_6f', 'Mixed_6g', 'Mixed_6h', 'Mixed_7a',
        'Mixed_7b', 'Mixed_7c', 'Mixed_7d']
    for index, endpoint in enumerate(all_endpoints):
      with tf.Graph().as_default():
        inputs = tf.random_uniform((batch_size, height, width, 3))
        out_tensor, end_points = inception.inception_v4_base(
            inputs, final_endpoint=endpoint)
        self.assertTrue(out_tensor.op.name.startswith(
            'InceptionV4/' + endpoint))
        self.assertItemsEqual(all_endpoints[:index+1], end_points.keys())
Example #6
Source File: inception_v4_test.py    From object_detection_with_tensorflow with MIT License 6 votes vote down vote up 
def testBuildOnlyUpToFinalEndpoint(self):
    batch_size = 5
    height, width = 299, 299
    all_endpoints = [
        'Conv2d_1a_3x3', 'Conv2d_2a_3x3', 'Conv2d_2b_3x3', 'Mixed_3a',
        'Mixed_4a', 'Mixed_5a', 'Mixed_5b', 'Mixed_5c', 'Mixed_5d',
        'Mixed_5e', 'Mixed_6a', 'Mixed_6b', 'Mixed_6c', 'Mixed_6d',
        'Mixed_6e', 'Mixed_6f', 'Mixed_6g', 'Mixed_6h', 'Mixed_7a',
        'Mixed_7b', 'Mixed_7c', 'Mixed_7d']
    for index, endpoint in enumerate(all_endpoints):
      with tf.Graph().as_default():
        inputs = tf.random_uniform((batch_size, height, width, 3))
        out_tensor, end_points = inception.inception_v4_base(
            inputs, final_endpoint=endpoint)
        self.assertTrue(out_tensor.op.name.startswith(
            'InceptionV4/' + endpoint))
        self.assertItemsEqual(all_endpoints[:index+1], end_points)
Example #7
Source File: inception_v4_test.py    From Optical-Flow-Guided-Feature with MIT License 6 votes vote down vote up 
def testBuildBaseNetwork(self):
    batch_size = 5
    height, width = 299, 299
    inputs = tf.random_uniform((batch_size, height, width, 3))
    net, end_points = inception.inception_v4_base(inputs)
    self.assertTrue(net.op.name.startswith(
        'InceptionV4/Mixed_7d'))
    self.assertListEqual(net.get_shape().as_list(), [batch_size, 8, 8, 1536])
    expected_endpoints = [
        'Conv2d_1a_3x3', 'Conv2d_2a_3x3', 'Conv2d_2b_3x3', 'Mixed_3a',
        'Mixed_4a', 'Mixed_5a', 'Mixed_5b', 'Mixed_5c', 'Mixed_5d',
        'Mixed_5e', 'Mixed_6a', 'Mixed_6b', 'Mixed_6c', 'Mixed_6d',
        'Mixed_6e', 'Mixed_6f', 'Mixed_6g', 'Mixed_6h', 'Mixed_7a',
        'Mixed_7b', 'Mixed_7c', 'Mixed_7d']
    self.assertItemsEqual(end_points.keys(), expected_endpoints)
    for name, op in end_points.iteritems():
      self.assertTrue(op.name.startswith('InceptionV4/' + name))
Example #8
Source File: inception_v4_test.py    From MBMD with MIT License 6 votes vote down vote up 
def testBuildOnlyUpToFinalEndpoint(self):
    batch_size = 5
    height, width = 299, 299
    all_endpoints = [
        'Conv2d_1a_3x3', 'Conv2d_2a_3x3', 'Conv2d_2b_3x3', 'Mixed_3a',
        'Mixed_4a', 'Mixed_5a', 'Mixed_5b', 'Mixed_5c', 'Mixed_5d',
        'Mixed_5e', 'Mixed_6a', 'Mixed_6b', 'Mixed_6c', 'Mixed_6d',
        'Mixed_6e', 'Mixed_6f', 'Mixed_6g', 'Mixed_6h', 'Mixed_7a',
        'Mixed_7b', 'Mixed_7c', 'Mixed_7d']
    for index, endpoint in enumerate(all_endpoints):
      with tf.Graph().as_default():
        inputs = tf.random_uniform((batch_size, height, width, 3))
        out_tensor, end_points = inception.inception_v4_base(
            inputs, final_endpoint=endpoint)
        self.assertTrue(out_tensor.op.name.startswith(
            'InceptionV4/' + endpoint))
        self.assertItemsEqual(all_endpoints[:index+1], end_points)
Example #9
Source File: inception_v4_test.py    From MBMD with MIT License 6 votes vote down vote up 
def testBuildBaseNetwork(self):
    batch_size = 5
    height, width = 299, 299
    inputs = tf.random_uniform((batch_size, height, width, 3))
    net, end_points = inception.inception_v4_base(inputs)
    self.assertTrue(net.op.name.startswith(
        'InceptionV4/Mixed_7d'))
    self.assertListEqual(net.get_shape().as_list(), [batch_size, 8, 8, 1536])
    expected_endpoints = [
        'Conv2d_1a_3x3', 'Conv2d_2a_3x3', 'Conv2d_2b_3x3', 'Mixed_3a',
        'Mixed_4a', 'Mixed_5a', 'Mixed_5b', 'Mixed_5c', 'Mixed_5d',
        'Mixed_5e', 'Mixed_6a', 'Mixed_6b', 'Mixed_6c', 'Mixed_6d',
        'Mixed_6e', 'Mixed_6f', 'Mixed_6g', 'Mixed_6h', 'Mixed_7a',
        'Mixed_7b', 'Mixed_7c', 'Mixed_7d']
    self.assertItemsEqual(end_points.keys(), expected_endpoints)
    for name, op in end_points.iteritems():
      self.assertTrue(op.name.startswith('InceptionV4/' + name))
Example #10
Source File: inception_v4_test.py    From object_detection_kitti with Apache License 2.0 6 votes vote down vote up 
def testBuildOnlyUpToFinalEndpoint(self):
    batch_size = 5
    height, width = 299, 299
    all_endpoints = [
        'Conv2d_1a_3x3', 'Conv2d_2a_3x3', 'Conv2d_2b_3x3', 'Mixed_3a',
        'Mixed_4a', 'Mixed_5a', 'Mixed_5b', 'Mixed_5c', 'Mixed_5d',
        'Mixed_5e', 'Mixed_6a', 'Mixed_6b', 'Mixed_6c', 'Mixed_6d',
        'Mixed_6e', 'Mixed_6f', 'Mixed_6g', 'Mixed_6h', 'Mixed_7a',
        'Mixed_7b', 'Mixed_7c', 'Mixed_7d']
    for index, endpoint in enumerate(all_endpoints):
      with tf.Graph().as_default():
        inputs = tf.random_uniform((batch_size, height, width, 3))
        out_tensor, end_points = inception.inception_v4_base(
            inputs, final_endpoint=endpoint)
        self.assertTrue(out_tensor.op.name.startswith(
            'InceptionV4/' + endpoint))
        self.assertItemsEqual(all_endpoints[:index+1], end_points)
Example #11
Source File: inception_v4_test.py    From Optical-Flow-Guided-Feature with MIT License 6 votes vote down vote up 
def testBuildOnlyUpToFinalEndpoint(self):
    batch_size = 5
    height, width = 299, 299
    all_endpoints = [
        'Conv2d_1a_3x3', 'Conv2d_2a_3x3', 'Conv2d_2b_3x3', 'Mixed_3a',
        'Mixed_4a', 'Mixed_5a', 'Mixed_5b', 'Mixed_5c', 'Mixed_5d',
        'Mixed_5e', 'Mixed_6a', 'Mixed_6b', 'Mixed_6c', 'Mixed_6d',
        'Mixed_6e', 'Mixed_6f', 'Mixed_6g', 'Mixed_6h', 'Mixed_7a',
        'Mixed_7b', 'Mixed_7c', 'Mixed_7d']
    for index, endpoint in enumerate(all_endpoints):
      with tf.Graph().as_default():
        inputs = tf.random_uniform((batch_size, height, width, 3))
        out_tensor, end_points = inception.inception_v4_base(
            inputs, final_endpoint=endpoint)
        self.assertTrue(out_tensor.op.name.startswith(
            'InceptionV4/' + endpoint))
        self.assertItemsEqual(all_endpoints[:index+1], end_points)
Example #12
Source File: inception_v4_test.py    From Translation-Invariant-Attacks with Apache License 2.0 6 votes vote down vote up 
def testBuildOnlyUpToFinalEndpoint(self):
    batch_size = 5
    height, width = 299, 299
    all_endpoints = [
        'Conv2d_1a_3x3', 'Conv2d_2a_3x3', 'Conv2d_2b_3x3', 'Mixed_3a',
        'Mixed_4a', 'Mixed_5a', 'Mixed_5b', 'Mixed_5c', 'Mixed_5d',
        'Mixed_5e', 'Mixed_6a', 'Mixed_6b', 'Mixed_6c', 'Mixed_6d',
        'Mixed_6e', 'Mixed_6f', 'Mixed_6g', 'Mixed_6h', 'Mixed_7a',
        'Mixed_7b', 'Mixed_7c', 'Mixed_7d']
    for index, endpoint in enumerate(all_endpoints):
      with tf.Graph().as_default():
        inputs = tf.random_uniform((batch_size, height, width, 3))
        out_tensor, end_points = inception.inception_v4_base(
            inputs, final_endpoint=endpoint)
        self.assertTrue(out_tensor.op.name.startswith(
            'InceptionV4/' + endpoint))
        self.assertItemsEqual(all_endpoints[:index+1], end_points)
Example #13
Source File: inception_v4_test.py    From Translation-Invariant-Attacks with Apache License 2.0 6 votes vote down vote up 
def testBuildBaseNetwork(self):
    batch_size = 5
    height, width = 299, 299
    inputs = tf.random_uniform((batch_size, height, width, 3))
    net, end_points = inception.inception_v4_base(inputs)
    self.assertTrue(net.op.name.startswith(
        'InceptionV4/Mixed_7d'))
    self.assertListEqual(net.get_shape().as_list(), [batch_size, 8, 8, 1536])
    expected_endpoints = [
        'Conv2d_1a_3x3', 'Conv2d_2a_3x3', 'Conv2d_2b_3x3', 'Mixed_3a',
        'Mixed_4a', 'Mixed_5a', 'Mixed_5b', 'Mixed_5c', 'Mixed_5d',
        'Mixed_5e', 'Mixed_6a', 'Mixed_6b', 'Mixed_6c', 'Mixed_6d',
        'Mixed_6e', 'Mixed_6f', 'Mixed_6g', 'Mixed_6h', 'Mixed_7a',
        'Mixed_7b', 'Mixed_7c', 'Mixed_7d']
    self.assertItemsEqual(end_points.keys(), expected_endpoints)
    for name, op in end_points.iteritems():
      self.assertTrue(op.name.startswith('InceptionV4/' + name))
Example #14
Source File: inception_v4_test.py    From tf_classification with MIT License 6 votes vote down vote up 
def testBuildOnlyUpToFinalEndpoint(self):
    batch_size = 5
    height, width = 299, 299
    all_endpoints = [
        'Conv2d_1a_3x3', 'Conv2d_2a_3x3', 'Conv2d_2b_3x3', 'Mixed_3a',
        'Mixed_4a', 'Mixed_5a', 'Mixed_5b', 'Mixed_5c', 'Mixed_5d',
        'Mixed_5e', 'Mixed_6a', 'Mixed_6b', 'Mixed_6c', 'Mixed_6d',
        'Mixed_6e', 'Mixed_6f', 'Mixed_6g', 'Mixed_6h', 'Mixed_7a',
        'Mixed_7b', 'Mixed_7c', 'Mixed_7d']
    for index, endpoint in enumerate(all_endpoints):
      with tf.Graph().as_default():
        inputs = tf.random_uniform((batch_size, height, width, 3))
        out_tensor, end_points = inception.inception_v4_base(
            inputs, final_endpoint=endpoint)
        self.assertTrue(out_tensor.op.name.startswith(
            'InceptionV4/' + endpoint))
        self.assertItemsEqual(all_endpoints[:index+1], end_points)
Example #15
Source File: inception_v4_test.py    From tf_classification with MIT License 6 votes vote down vote up 
def testBuildBaseNetwork(self):
    batch_size = 5
    height, width = 299, 299
    inputs = tf.random_uniform((batch_size, height, width, 3))
    net, end_points = inception.inception_v4_base(inputs)
    self.assertTrue(net.op.name.startswith(
        'InceptionV4/Mixed_7d'))
    self.assertListEqual(net.get_shape().as_list(), [batch_size, 8, 8, 1536])
    expected_endpoints = [
        'Conv2d_1a_3x3', 'Conv2d_2a_3x3', 'Conv2d_2b_3x3', 'Mixed_3a',
        'Mixed_4a', 'Mixed_5a', 'Mixed_5b', 'Mixed_5c', 'Mixed_5d',
        'Mixed_5e', 'Mixed_6a', 'Mixed_6b', 'Mixed_6c', 'Mixed_6d',
        'Mixed_6e', 'Mixed_6f', 'Mixed_6g', 'Mixed_6h', 'Mixed_7a',
        'Mixed_7b', 'Mixed_7c', 'Mixed_7d']
    self.assertItemsEqual(end_points.keys(), expected_endpoints)
    for name, op in end_points.iteritems():
      self.assertTrue(op.name.startswith('InceptionV4/' + name))
Example #16
Source File: inception_v4_test.py    From vehicle-triplet-reid with MIT License 6 votes vote down vote up 
def testBuildBaseNetwork(self):
    batch_size = 5
    height, width = 299, 299
    inputs = tf.random_uniform((batch_size, height, width, 3))
    net, end_points = inception.inception_v4_base(inputs)
    self.assertTrue(net.op.name.startswith(
        'InceptionV4/Mixed_7d'))
    self.assertListEqual(net.get_shape().as_list(), [batch_size, 8, 8, 1536])
    expected_endpoints = [
        'Conv2d_1a_3x3', 'Conv2d_2a_3x3', 'Conv2d_2b_3x3', 'Mixed_3a',
        'Mixed_4a', 'Mixed_5a', 'Mixed_5b', 'Mixed_5c', 'Mixed_5d',
        'Mixed_5e', 'Mixed_6a', 'Mixed_6b', 'Mixed_6c', 'Mixed_6d',
        'Mixed_6e', 'Mixed_6f', 'Mixed_6g', 'Mixed_6h', 'Mixed_7a',
        'Mixed_7b', 'Mixed_7c', 'Mixed_7d']
    self.assertItemsEqual(end_points.keys(), expected_endpoints)
    for name, op in end_points.iteritems():
      self.assertTrue(op.name.startswith('InceptionV4/' + name))
Example #17
Source File: inception_v4_test.py    From TwinGAN with Apache License 2.0 6 votes vote down vote up 
def testBuildBaseNetwork(self):
    batch_size = 5
    height, width = 299, 299
    inputs = tf.random_uniform((batch_size, height, width, 3))
    net, end_points = inception.inception_v4_base(inputs)
    self.assertTrue(net.op.name.startswith(
        'InceptionV4/Mixed_7d'))
    self.assertListEqual(net.get_shape().as_list(), [batch_size, 8, 8, 1536])
    expected_endpoints = [
        'Conv2d_1a_3x3', 'Conv2d_2a_3x3', 'Conv2d_2b_3x3', 'Mixed_3a',
        'Mixed_4a', 'Mixed_5a', 'Mixed_5b', 'Mixed_5c', 'Mixed_5d',
        'Mixed_5e', 'Mixed_6a', 'Mixed_6b', 'Mixed_6c', 'Mixed_6d',
        'Mixed_6e', 'Mixed_6f', 'Mixed_6g', 'Mixed_6h', 'Mixed_7a',
        'Mixed_7b', 'Mixed_7c', 'Mixed_7d']
    self.assertItemsEqual(end_points.keys(), expected_endpoints)
    for name, op in end_points.iteritems():
      self.assertTrue(op.name.startswith('InceptionV4/' + name))
Example #18
Source File: inception_v4_test.py    From style_swap_tensorflow with Apache License 2.0 6 votes vote down vote up 
def testBuildOnlyUpToFinalEndpoint(self):
    batch_size = 5
    height, width = 299, 299
    all_endpoints = [
        'Conv2d_1a_3x3', 'Conv2d_2a_3x3', 'Conv2d_2b_3x3', 'Mixed_3a',
        'Mixed_4a', 'Mixed_5a', 'Mixed_5b', 'Mixed_5c', 'Mixed_5d',
        'Mixed_5e', 'Mixed_6a', 'Mixed_6b', 'Mixed_6c', 'Mixed_6d',
        'Mixed_6e', 'Mixed_6f', 'Mixed_6g', 'Mixed_6h', 'Mixed_7a',
        'Mixed_7b', 'Mixed_7c', 'Mixed_7d']
    for index, endpoint in enumerate(all_endpoints):
      with tf.Graph().as_default():
        inputs = tf.random_uniform((batch_size, height, width, 3))
        out_tensor, end_points = inception.inception_v4_base(
            inputs, final_endpoint=endpoint)
        self.assertTrue(out_tensor.op.name.startswith(
            'InceptionV4/' + endpoint))
        self.assertItemsEqual(all_endpoints[:index+1], end_points)
Example #19
Source File: inception_v4_test.py    From style_swap_tensorflow with Apache License 2.0 6 votes vote down vote up 
def testBuildBaseNetwork(self):
    batch_size = 5
    height, width = 299, 299
    inputs = tf.random_uniform((batch_size, height, width, 3))
    net, end_points = inception.inception_v4_base(inputs)
    self.assertTrue(net.op.name.startswith(
        'InceptionV4/Mixed_7d'))
    self.assertListEqual(net.get_shape().as_list(), [batch_size, 8, 8, 1536])
    expected_endpoints = [
        'Conv2d_1a_3x3', 'Conv2d_2a_3x3', 'Conv2d_2b_3x3', 'Mixed_3a',
        'Mixed_4a', 'Mixed_5a', 'Mixed_5b', 'Mixed_5c', 'Mixed_5d',
        'Mixed_5e', 'Mixed_6a', 'Mixed_6b', 'Mixed_6c', 'Mixed_6d',
        'Mixed_6e', 'Mixed_6f', 'Mixed_6g', 'Mixed_6h', 'Mixed_7a',
        'Mixed_7b', 'Mixed_7c', 'Mixed_7d']
    self.assertItemsEqual(end_points.keys(), expected_endpoints)
    for name, op in end_points.iteritems():
      self.assertTrue(op.name.startswith('InceptionV4/' + name))
Example #20
Source File: inception_v4_test.py    From Targeted-Adversarial-Attack with Apache License 2.0 6 votes vote down vote up 
def testBuildOnlyUpToFinalEndpoint(self):
    batch_size = 5
    height, width = 299, 299
    all_endpoints = [
        'Conv2d_1a_3x3', 'Conv2d_2a_3x3', 'Conv2d_2b_3x3', 'Mixed_3a',
        'Mixed_4a', 'Mixed_5a', 'Mixed_5b', 'Mixed_5c', 'Mixed_5d',
        'Mixed_5e', 'Mixed_6a', 'Mixed_6b', 'Mixed_6c', 'Mixed_6d',
        'Mixed_6e', 'Mixed_6f', 'Mixed_6g', 'Mixed_6h', 'Mixed_7a',
        'Mixed_7b', 'Mixed_7c', 'Mixed_7d']
    for index, endpoint in enumerate(all_endpoints):
      with tf.Graph().as_default():
        inputs = tf.random_uniform((batch_size, height, width, 3))
        out_tensor, end_points = inception.inception_v4_base(
            inputs, final_endpoint=endpoint)
        self.assertTrue(out_tensor.op.name.startswith(
            'InceptionV4/' + endpoint))
        self.assertItemsEqual(all_endpoints[:index+1], end_points)
Example #21
Source File: inception_v4_test.py    From Targeted-Adversarial-Attack with Apache License 2.0 6 votes vote down vote up 
def testBuildBaseNetwork(self):
    batch_size = 5
    height, width = 299, 299
    inputs = tf.random_uniform((batch_size, height, width, 3))
    net, end_points = inception.inception_v4_base(inputs)
    self.assertTrue(net.op.name.startswith(
        'InceptionV4/Mixed_7d'))
    self.assertListEqual(net.get_shape().as_list(), [batch_size, 8, 8, 1536])
    expected_endpoints = [
        'Conv2d_1a_3x3', 'Conv2d_2a_3x3', 'Conv2d_2b_3x3', 'Mixed_3a',
        'Mixed_4a', 'Mixed_5a', 'Mixed_5b', 'Mixed_5c', 'Mixed_5d',
        'Mixed_5e', 'Mixed_6a', 'Mixed_6b', 'Mixed_6c', 'Mixed_6d',
        'Mixed_6e', 'Mixed_6f', 'Mixed_6g', 'Mixed_6h', 'Mixed_7a',
        'Mixed_7b', 'Mixed_7c', 'Mixed_7d']
    self.assertItemsEqual(end_points.keys(), expected_endpoints)
    for name, op in end_points.iteritems():
      self.assertTrue(op.name.startswith('InceptionV4/' + name))
Example #22
Source File: inception_v4_test.py    From tumblr-emotions with Apache License 2.0 6 votes vote down vote up 
def testBuildOnlyUpToFinalEndpoint(self):
    batch_size = 5
    height, width = 299, 299
    all_endpoints = [
        'Conv2d_1a_3x3', 'Conv2d_2a_3x3', 'Conv2d_2b_3x3', 'Mixed_3a',
        'Mixed_4a', 'Mixed_5a', 'Mixed_5b', 'Mixed_5c', 'Mixed_5d',
        'Mixed_5e', 'Mixed_6a', 'Mixed_6b', 'Mixed_6c', 'Mixed_6d',
        'Mixed_6e', 'Mixed_6f', 'Mixed_6g', 'Mixed_6h', 'Mixed_7a',
        'Mixed_7b', 'Mixed_7c', 'Mixed_7d']
    for index, endpoint in enumerate(all_endpoints):
      with tf.Graph().as_default():
        inputs = tf.random_uniform((batch_size, height, width, 3))
        out_tensor, end_points = inception.inception_v4_base(
            inputs, final_endpoint=endpoint)
        self.assertTrue(out_tensor.op.name.startswith(
            'InceptionV4/' + endpoint))
        self.assertItemsEqual(all_endpoints[:index+1], end_points)
Example #23
Source File: inception_v4_test.py    From tumblr-emotions with Apache License 2.0 6 votes vote down vote up 
def testBuildBaseNetwork(self):
    batch_size = 5
    height, width = 299, 299
    inputs = tf.random_uniform((batch_size, height, width, 3))
    net, end_points = inception.inception_v4_base(inputs)
    self.assertTrue(net.op.name.startswith(
        'InceptionV4/Mixed_7d'))
    self.assertListEqual(net.get_shape().as_list(), [batch_size, 8, 8, 1536])
    expected_endpoints = [
        'Conv2d_1a_3x3', 'Conv2d_2a_3x3', 'Conv2d_2b_3x3', 'Mixed_3a',
        'Mixed_4a', 'Mixed_5a', 'Mixed_5b', 'Mixed_5c', 'Mixed_5d',
        'Mixed_5e', 'Mixed_6a', 'Mixed_6b', 'Mixed_6c', 'Mixed_6d',
        'Mixed_6e', 'Mixed_6f', 'Mixed_6g', 'Mixed_6h', 'Mixed_7a',
        'Mixed_7b', 'Mixed_7c', 'Mixed_7d']
    self.assertItemsEqual(end_points.keys(), expected_endpoints)
    for name, op in end_points.iteritems():
      self.assertTrue(op.name.startswith('InceptionV4/' + name))
Example #24
Source File: inception_v4_test.py    From tensorflow_yolo2 with MIT License 6 votes vote down vote up 
def testBuildOnlyUpToFinalEndpoint(self):
    batch_size = 5
    height, width = 299, 299
    all_endpoints = [
        'Conv2d_1a_3x3', 'Conv2d_2a_3x3', 'Conv2d_2b_3x3', 'Mixed_3a',
        'Mixed_4a', 'Mixed_5a', 'Mixed_5b', 'Mixed_5c', 'Mixed_5d',
        'Mixed_5e', 'Mixed_6a', 'Mixed_6b', 'Mixed_6c', 'Mixed_6d',
        'Mixed_6e', 'Mixed_6f', 'Mixed_6g', 'Mixed_6h', 'Mixed_7a',
        'Mixed_7b', 'Mixed_7c', 'Mixed_7d']
    for index, endpoint in enumerate(all_endpoints):
      with tf.Graph().as_default():
        inputs = tf.random_uniform((batch_size, height, width, 3))
        out_tensor, end_points = inception.inception_v4_base(
            inputs, final_endpoint=endpoint)
        self.assertTrue(out_tensor.op.name.startswith(
            'InceptionV4/' + endpoint))
        self.assertItemsEqual(all_endpoints[:index+1], end_points)
Example #25
Source File: inception_v4_test.py    From tensorflow_yolo2 with MIT License 6 votes vote down vote up 
def testBuildBaseNetwork(self):
    batch_size = 5
    height, width = 299, 299
    inputs = tf.random_uniform((batch_size, height, width, 3))
    net, end_points = inception.inception_v4_base(inputs)
    self.assertTrue(net.op.name.startswith(
        'InceptionV4/Mixed_7d'))
    self.assertListEqual(net.get_shape().as_list(), [batch_size, 8, 8, 1536])
    expected_endpoints = [
        'Conv2d_1a_3x3', 'Conv2d_2a_3x3', 'Conv2d_2b_3x3', 'Mixed_3a',
        'Mixed_4a', 'Mixed_5a', 'Mixed_5b', 'Mixed_5c', 'Mixed_5d',
        'Mixed_5e', 'Mixed_6a', 'Mixed_6b', 'Mixed_6c', 'Mixed_6d',
        'Mixed_6e', 'Mixed_6f', 'Mixed_6g', 'Mixed_6h', 'Mixed_7a',
        'Mixed_7b', 'Mixed_7c', 'Mixed_7d']
    self.assertItemsEqual(end_points.keys(), expected_endpoints)
    for name, op in end_points.iteritems():
      self.assertTrue(op.name.startswith('InceptionV4/' + name))
Example #26
Source File: inception_v4_test.py    From MAX-Image-Segmenter with Apache License 2.0 6 votes vote down vote up 
def testBuildOnlyUpToFinalEndpoint(self):
    batch_size = 5
    height, width = 299, 299
    all_endpoints = [
        'Conv2d_1a_3x3', 'Conv2d_2a_3x3', 'Conv2d_2b_3x3', 'Mixed_3a',
        'Mixed_4a', 'Mixed_5a', 'Mixed_5b', 'Mixed_5c', 'Mixed_5d',
        'Mixed_5e', 'Mixed_6a', 'Mixed_6b', 'Mixed_6c', 'Mixed_6d',
        'Mixed_6e', 'Mixed_6f', 'Mixed_6g', 'Mixed_6h', 'Mixed_7a',
        'Mixed_7b', 'Mixed_7c', 'Mixed_7d']
    for index, endpoint in enumerate(all_endpoints):
      with tf.Graph().as_default():
        inputs = tf.random_uniform((batch_size, height, width, 3))
        out_tensor, end_points = inception.inception_v4_base(
            inputs, final_endpoint=endpoint)
        self.assertTrue(out_tensor.op.name.startswith(
            'InceptionV4/' + endpoint))
        self.assertItemsEqual(all_endpoints[:index+1], end_points.keys())
Example #27
Source File: inception_v4_test.py    From MAX-Image-Segmenter with Apache License 2.0 6 votes vote down vote up 
def testBuildBaseNetwork(self):
    batch_size = 5
    height, width = 299, 299
    inputs = tf.random_uniform((batch_size, height, width, 3))
    net, end_points = inception.inception_v4_base(inputs)
    self.assertTrue(net.op.name.startswith(
        'InceptionV4/Mixed_7d'))
    self.assertListEqual(net.get_shape().as_list(), [batch_size, 8, 8, 1536])
    expected_endpoints = [
        'Conv2d_1a_3x3', 'Conv2d_2a_3x3', 'Conv2d_2b_3x3', 'Mixed_3a',
        'Mixed_4a', 'Mixed_5a', 'Mixed_5b', 'Mixed_5c', 'Mixed_5d',
        'Mixed_5e', 'Mixed_6a', 'Mixed_6b', 'Mixed_6c', 'Mixed_6d',
        'Mixed_6e', 'Mixed_6f', 'Mixed_6g', 'Mixed_6h', 'Mixed_7a',
        'Mixed_7b', 'Mixed_7c', 'Mixed_7d']
    self.assertItemsEqual(end_points.keys(), expected_endpoints)
    for name, op in end_points.items():
      self.assertTrue(op.name.startswith('InceptionV4/' + name))
Example #28
Source File: inception_v4_test.py    From MobileNet with Apache License 2.0 6 votes vote down vote up 
def testBuildOnlyUpToFinalEndpoint(self):
    batch_size = 5
    height, width = 299, 299
    all_endpoints = [
        'Conv2d_1a_3x3', 'Conv2d_2a_3x3', 'Conv2d_2b_3x3', 'Mixed_3a',
        'Mixed_4a', 'Mixed_5a', 'Mixed_5b', 'Mixed_5c', 'Mixed_5d',
        'Mixed_5e', 'Mixed_6a', 'Mixed_6b', 'Mixed_6c', 'Mixed_6d',
        'Mixed_6e', 'Mixed_6f', 'Mixed_6g', 'Mixed_6h', 'Mixed_7a',
        'Mixed_7b', 'Mixed_7c', 'Mixed_7d']
    for index, endpoint in enumerate(all_endpoints):
      with tf.Graph().as_default():
        inputs = tf.random_uniform((batch_size, height, width, 3))
        out_tensor, end_points = inception.inception_v4_base(
            inputs, final_endpoint=endpoint)
        self.assertTrue(out_tensor.op.name.startswith(
            'InceptionV4/' + endpoint))
        self.assertItemsEqual(all_endpoints[:index+1], end_points)
Example #29
Source File: inception_v4_test.py    From MobileNet with Apache License 2.0 6 votes vote down vote up 
def testBuildBaseNetwork(self):
    batch_size = 5
    height, width = 299, 299
    inputs = tf.random_uniform((batch_size, height, width, 3))
    net, end_points = inception.inception_v4_base(inputs)
    self.assertTrue(net.op.name.startswith(
        'InceptionV4/Mixed_7d'))
    self.assertListEqual(net.get_shape().as_list(), [batch_size, 8, 8, 1536])
    expected_endpoints = [
        'Conv2d_1a_3x3', 'Conv2d_2a_3x3', 'Conv2d_2b_3x3', 'Mixed_3a',
        'Mixed_4a', 'Mixed_5a', 'Mixed_5b', 'Mixed_5c', 'Mixed_5d',
        'Mixed_5e', 'Mixed_6a', 'Mixed_6b', 'Mixed_6c', 'Mixed_6d',
        'Mixed_6e', 'Mixed_6f', 'Mixed_6g', 'Mixed_6h', 'Mixed_7a',
        'Mixed_7b', 'Mixed_7c', 'Mixed_7d']
    self.assertItemsEqual(end_points.keys(), expected_endpoints)
    for name, op in end_points.iteritems():
      self.assertTrue(op.name.startswith('InceptionV4/' + name))
Example #30
Source File: inception_v4_test.py    From hops-tensorflow with Apache License 2.0 6 votes vote down vote up 
def testBuildOnlyUpToFinalEndpoint(self):
    batch_size = 5
    height, width = 299, 299
    all_endpoints = [
        'Conv2d_1a_3x3', 'Conv2d_2a_3x3', 'Conv2d_2b_3x3', 'Mixed_3a',
        'Mixed_4a', 'Mixed_5a', 'Mixed_5b', 'Mixed_5c', 'Mixed_5d',
        'Mixed_5e', 'Mixed_6a', 'Mixed_6b', 'Mixed_6c', 'Mixed_6d',
        'Mixed_6e', 'Mixed_6f', 'Mixed_6g', 'Mixed_6h', 'Mixed_7a',
        'Mixed_7b', 'Mixed_7c', 'Mixed_7d']
    for index, endpoint in enumerate(all_endpoints):
      with tf.Graph().as_default():
        inputs = tf.random_uniform((batch_size, height, width, 3))
        out_tensor, end_points = inception.inception_v4_base(
            inputs, final_endpoint=endpoint)
        self.assertTrue(out_tensor.op.name.startswith(
            'InceptionV4/' + endpoint))
        self.assertItemsEqual(all_endpoints[:index+1], end_points)