Python tf_spec_structure Exemples

Exemple #1

 def testStructureFromTensor(self):
     with self.test_session():
         inputs = tf.constant(_rand(1, 18, 19, 5))
         spec = "net = Cr(64, [5, 5])"
         outputs = specs.create_net(spec, inputs)
         tf.initialize_all_variables().run()
         result = outputs.eval()
         self.assertEqual(tuple(result.shape), (1, 18, 19, 64))
         self.assertEqual(summaries.tf_spec_structure(spec, inputs),
                          "_ var conv var biasadd relu")

Exemple #2

Fichier : summaries_test.py Projet : moolighty/tensorflow

 def testStructureFromTensor(self):
   with self.test_session():
     inputs = tf.constant(_rand(1, 18, 19, 5))
     spec = "net = Cr(64, [5, 5])"
     outputs = specs.create_net(spec, inputs)
     tf.global_variables_initializer().run()
     result = outputs.eval()
     self.assertEqual(tuple(result.shape), (1, 18, 19, 64))
     self.assertEqual(summaries.tf_spec_structure(spec, inputs),
                      "_ variablev2 conv variablev2 biasadd relu")

Exemple #3

Fichier : specs_test.py Projet : 0xheart0/tensorflow

 def testSimpleConv(self):
     with self.test_session():
         inputs = constant_op.constant(_rand(1, 18, 19, 5))
         spec = "net = Cr(64, [5, 5])"
         outputs = specs.create_net(spec, inputs)
         self.assertEqual(outputs.get_shape().as_list(), [1, 18, 19, 64])
         variables.global_variables_initializer().run()
         result = outputs.eval()
         self.assertEqual(tuple(result.shape), (1, 18, 19, 64))
         self.assertEqual(summaries.tf_spec_structure(spec, inputs),
                          "_ variablev2 conv variablev2 biasadd relu")

Exemple #4

Fichier : specs_test.py Projet : 821760408-sp/tensorflow

 def testMpPower(self):
   with self.test_session():
     inputs = tf.constant(_rand(1, 64, 64, 5))
     spec = "M2 = Mp([2, 2]); net = M2**3"
     outputs = specs.create_net(spec, inputs)
     self.assertEqual(outputs.get_shape().as_list(), [1, 8, 8, 5])
     tf.initialize_all_variables().run()
     result = outputs.eval()
     self.assertEqual(tuple(result.shape), (1, 8, 8, 5))
     self.assertEqual(summaries.tf_spec_structure(spec, inputs),
                      "_ maxpool maxpool maxpool")

Exemple #5

Fichier : specs_test.py Projet : 821760408-sp/tensorflow

 def testSimpleConv(self):
   with self.test_session():
     inputs = tf.constant(_rand(1, 18, 19, 5))
     spec = "net = Cr(64, [5, 5])"
     outputs = specs.create_net(spec, inputs)
     self.assertEqual(outputs.get_shape().as_list(), [1, 18, 19, 64])
     tf.initialize_all_variables().run()
     result = outputs.eval()
     self.assertEqual(tuple(result.shape), (1, 18, 19, 64))
     self.assertEqual(summaries.tf_spec_structure(spec, inputs),
                      "_ var conv var biasadd relu")

Exemple #6

Fichier : specs_test.py Projet : 0xheart0/tensorflow

 def testMpPower(self):
     with self.test_session():
         inputs = constant_op.constant(_rand(1, 64, 64, 5))
         spec = "M2 = Mp([2, 2]); net = M2**3"
         outputs = specs.create_net(spec, inputs)
         self.assertEqual(outputs.get_shape().as_list(), [1, 8, 8, 5])
         variables.global_variables_initializer().run()
         result = outputs.eval()
         self.assertEqual(tuple(result.shape), (1, 8, 8, 5))
         self.assertEqual(summaries.tf_spec_structure(spec, inputs),
                          "_ maxpool maxpool maxpool")

Exemple #7

Fichier : specs_test.py Projet : PaullMP/TensorFlowT

 def testImport(self):
     with self.test_session():
         inputs = tf.constant(_rand(10, 20))
         spec = "S = Import('import tensorflow as tf; f = tf.nn.sigmoid')"
         spec += "; net = S | S"
         outputs = specs.create_net(spec, inputs)
         self.assertEqual(outputs.get_shape().as_list(), [10, 20])
         tf.initialize_all_variables().run()
         result = outputs.eval()
         self.assertEqual(tuple(result.shape), (10, 20))
         self.assertEqual(summaries.tf_spec_structure(spec, inputs),
                          "_ sig sig")

Exemple #8

Fichier : specs_test.py Projet : 1000sprites/tensorflow

 def testImport(self):
   with self.test_session():
     inputs = constant_op.constant(_rand(10, 20))
     spec = ("S = Import('from tensorflow.python.ops" +
             " import math_ops; f = math_ops.sigmoid')")
     spec += "; net = S | S"
     outputs = specs.create_net(spec, inputs)
     self.assertEqual(outputs.get_shape().as_list(), [10, 20])
     variables.global_variables_initializer().run()
     result = outputs.eval()
     self.assertEqual(tuple(result.shape), (10, 20))
     self.assertEqual(summaries.tf_spec_structure(spec, inputs), "_ sig sig")

Exemple #9

Fichier : specs_test.py Projet : qingfeng8260/tensorflow_installpack

 def testImport(self):
   with self.cached_session():
     inputs = constant_op.constant(_rand(10, 20))
     spec = ("S = Import('from tensorflow.python.ops" +
             " import math_ops; f = math_ops.sigmoid')")
     spec += "; net = S | S"
     outputs = specs.create_net(spec, inputs)
     self.assertEqual(outputs.get_shape().as_list(), [10, 20])
     variables.global_variables_initializer().run()
     result = outputs.eval()
     self.assertEqual(tuple(result.shape), (10, 20))
     self.assertEqual(summaries.tf_spec_structure(spec, inputs), "_ sig sig")

Exemple #10

Fichier : specs_test.py Projet : 821760408-sp/tensorflow

 def testAdd(self):
   with self.test_session():
     inputs = tf.constant(_rand(17, 55))
     spec = "net = Fs(10) + Fr(10)"
     outputs = specs.create_net(spec, inputs)
     self.assertEqual(outputs.get_shape().as_list(), [17, 10])
     tf.initialize_all_variables().run()
     result = outputs.eval()
     self.assertEqual(tuple(result.shape), (17, 10))
     self.assertEqual(summaries.tf_spec_structure(spec, inputs),
                      "_ var dot var biasadd sig "
                      "<> var dot var biasadd relu add")

Exemple #11

Fichier : specs_test.py Projet : 821760408-sp/tensorflow

 def testImport(self):
   with self.test_session():
     inputs = tf.constant(_rand(10, 20))
     spec = "S = Import('import tensorflow as tf; f = tf.nn.sigmoid')"
     spec += "; net = S | S"
     outputs = specs.create_net(spec, inputs)
     self.assertEqual(outputs.get_shape().as_list(), [10, 20])
     tf.initialize_all_variables().run()
     result = outputs.eval()
     self.assertEqual(tuple(result.shape), (10, 20))
     self.assertEqual(summaries.tf_spec_structure(spec, inputs),
                      "_ sig sig")

Exemple #12

Fichier : specs_test.py Projet : 821760408-sp/tensorflow

 def testConc(self):
   with self.test_session():
     inputs = tf.constant(_rand(10, 20))
     spec = "net = Conc(1, Fs(20), Fs(10))"
     outputs = specs.create_net(spec, inputs)
     self.assertEqual(outputs.get_shape().as_list(), [10, 30])
     tf.initialize_all_variables().run()
     result = outputs.eval()
     self.assertEqual(tuple(result.shape), (10, 30))
     self.assertEqual(summaries.tf_spec_structure(spec, inputs),
                      "_ _ var dot var biasadd sig "
                      "<> var dot var biasadd sig concat")

Exemple #13

Fichier : summaries_test.py Projet : zhaosv/tensorflow

 def testStructure(self):
     with self.test_session():
         inputs_shape = (1, 18, 19, 5)
         inputs = tf.constant(_rand(*inputs_shape))
         spec = "net = Cr(64, [5, 5])"
         outputs = specs.create_net(spec, inputs)
         tf.global_variables_initializer().run()
         result = outputs.eval()
         self.assertEqual(tuple(result.shape), (1, 18, 19, 64))
         self.assertEqual(
             summaries.tf_spec_structure(spec, input_shape=inputs_shape),
             "_ variablev2 conv variablev2 biasadd relu")

Exemple #14

Fichier : specs_test.py Projet : 821760408-sp/tensorflow

 def testAbbrevPower(self):
   with self.test_session():
     inputs = tf.constant(_rand(1, 64, 64, 5))
     spec = "C3 = Cr([3, 3]); M2 = Mp([2, 2]); net = (C3(5) | M2)**3"
     outputs = specs.create_net(spec, inputs)
     self.assertEqual(outputs.get_shape().as_list(), [1, 8, 8, 5])
     tf.initialize_all_variables().run()
     result = outputs.eval()
     self.assertEqual(tuple(result.shape), (1, 8, 8, 5))
     self.assertEqual(summaries.tf_spec_structure(spec, inputs),
                      "_ var conv var biasadd relu maxpool var conv var"
                      " biasadd relu maxpool var conv var"
                      " biasadd relu maxpool")

Exemple #15

Fichier : specs_test.py Projet : 821760408-sp/tensorflow

 def testAutoFunction(self):
   with self.test_session():
     inputs = tf.constant(_rand(1, 18, 19, 5))
     with specs.ops:
       # pylint: disable=undefined-variable
       net = SL.conv2d(64, 5)
     outputs = net.funcall(inputs)
     self.assertEqual(outputs.get_shape().as_list(), [1, 18, 19, 64])
     tf.initialize_all_variables().run()
     result = outputs.eval()
     self.assertEqual(tuple(result.shape), (1, 18, 19, 64))
     self.assertEqual(summaries.tf_spec_structure("net = Cr(64, 5)", inputs),
                      "_ var conv var biasadd relu")

Exemple #16

Fichier : specs_test.py Projet : Ajaycs99/tensorflow

 def testConc(self):
   with self.cached_session():
     inputs = constant_op.constant(_rand(10, 20))
     spec = "net = Conc(1, Fs(20), Fs(10))"
     outputs = specs.create_net(spec, inputs)
     self.assertEqual(outputs.get_shape().as_list(), [10, 30])
     variables.global_variables_initializer().run()
     result = outputs.eval()
     self.assertEqual(tuple(result.shape), (10, 30))
     self.assertEqual(
         summaries.tf_spec_structure(spec, inputs),
         "_ variablev2 dot variablev2 biasadd sig "
         "<> variablev2 dot variablev2 biasadd sig _ concatv2")

Exemple #17

Fichier : specs_test.py Projet : 0xheart0/tensorflow

 def testAdd(self):
     with self.test_session():
         inputs = constant_op.constant(_rand(17, 55))
         spec = "net = Fs(10) + Fr(10)"
         outputs = specs.create_net(spec, inputs)
         self.assertEqual(outputs.get_shape().as_list(), [17, 10])
         variables.global_variables_initializer().run()
         result = outputs.eval()
         self.assertEqual(tuple(result.shape), (17, 10))
         self.assertEqual(
             summaries.tf_spec_structure(spec, inputs),
             "_ variablev2 dot variablev2 biasadd sig "
             "<> variablev2 dot variablev2 biasadd relu add")

Exemple #18

Fichier : specs_test.py Projet : 0xheart0/tensorflow

 def testConc(self):
     with self.test_session():
         inputs = constant_op.constant(_rand(10, 20))
         spec = "net = Conc(1, Fs(20), Fs(10))"
         outputs = specs.create_net(spec, inputs)
         self.assertEqual(outputs.get_shape().as_list(), [10, 30])
         variables.global_variables_initializer().run()
         result = outputs.eval()
         self.assertEqual(tuple(result.shape), (10, 30))
         self.assertEqual(
             summaries.tf_spec_structure(spec, inputs),
             "_ variablev2 dot variablev2 biasadd sig "
             "<> variablev2 dot variablev2 biasadd sig _ concatv2")

Exemple #19

Fichier : specs_test.py Projet : PaullMP/TensorFlowT

 def testAutoFunction(self):
     with self.test_session():
         inputs = tf.constant(_rand(1, 18, 19, 5))
         with specs.ops:
             # pylint: disable=undefined-variable
             net = SL.conv2d(64, 5)
         outputs = net.funcall(inputs)
         self.assertEqual(outputs.get_shape().as_list(), [1, 18, 19, 64])
         tf.initialize_all_variables().run()
         result = outputs.eval()
         self.assertEqual(tuple(result.shape), (1, 18, 19, 64))
         self.assertEqual(
             summaries.tf_spec_structure("net = Cr(64, 5)", inputs),
             "_ var conv var biasadd relu")

Exemple #20

Fichier : specs_test.py Projet : PaullMP/TensorFlowT

 def testAbbrevPower(self):
     with self.test_session():
         inputs = tf.constant(_rand(1, 64, 64, 5))
         spec = "C3 = Cr([3, 3]); M2 = Mp([2, 2]); net = (C3(5) | M2)**3"
         outputs = specs.create_net(spec, inputs)
         self.assertEqual(outputs.get_shape().as_list(), [1, 8, 8, 5])
         tf.initialize_all_variables().run()
         result = outputs.eval()
         self.assertEqual(tuple(result.shape), (1, 8, 8, 5))
         self.assertEqual(
             summaries.tf_spec_structure(spec, inputs),
             "_ var conv var biasadd relu maxpool var conv var"
             " biasadd relu maxpool var conv var"
             " biasadd relu maxpool")

Exemple #21

Fichier : specs_test.py Projet : 1000sprites/tensorflow

 def testAbbrevPower2(self):
   with self.test_session():
     inputs = constant_op.constant(_rand(1, 64, 64, 5))
     spec = "C3 = Cr(_1=[3, 3]); M2 = Mp([2, 2]);"
     spec += "net = (C3(_0=5) | M2)**3"
     outputs = specs.create_net(spec, inputs)
     self.assertEqual(outputs.get_shape().as_list(), [1, 8, 8, 5])
     variables.global_variables_initializer().run()
     result = outputs.eval()
     self.assertEqual(tuple(result.shape), (1, 8, 8, 5))
     self.assertEqual(
         summaries.tf_spec_structure(spec, inputs),
         "_ variablev2 conv variablev2 biasadd relu maxpool"
         " variablev2 conv variablev2 biasadd relu"
         " maxpool variablev2 conv variablev2 biasadd relu"
         " maxpool")

Exemple #22

Fichier : specs_test.py Projet : 0xheart0/tensorflow

 def testAbbrevPower2(self):
     with self.test_session():
         inputs = constant_op.constant(_rand(1, 64, 64, 5))
         spec = "C3 = Cr(_1=[3, 3]); M2 = Mp([2, 2]);"
         spec += "net = (C3(_0=5) | M2)**3"
         outputs = specs.create_net(spec, inputs)
         self.assertEqual(outputs.get_shape().as_list(), [1, 8, 8, 5])
         variables.global_variables_initializer().run()
         result = outputs.eval()
         self.assertEqual(tuple(result.shape), (1, 8, 8, 5))
         self.assertEqual(
             summaries.tf_spec_structure(spec, inputs),
             "_ variablev2 conv variablev2 biasadd relu maxpool"
             " variablev2 conv variablev2 biasadd relu"
             " maxpool variablev2 conv variablev2 biasadd relu"
             " maxpool")