Making linter changes and removing un necessary files.

Squashed commit of the following: commit 1802f8a Author: Arafatk <arafat.da.khan@gmail.com> Date: Sat Mar 4 23:47:21 2017 +0530 Removing unnecessary file writing spec. commit 41dd55f Author: Arafatk <arafat.da.khan@gmail.com> Date: Sat Mar 4 23:40:13 2017 +0530 Adding Linter Changes to Specs. commit 23c6833 Author: Arafatk <arafat.da.khan@gmail.com> Date: Sat Mar 4 23:36:48 2017 +0530 Adding Linter changes.
arafatkatze · Mar 5, 2017 · ecf1954 · ecf1954
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diff --git a/abc b/abc
diff --git a/ext/sciruby/tensorflow_c/abc b/ext/sciruby/tensorflow_c/abc
diff --git a/ext/sciruby/tensorflow_c/converter.py b/ext/sciruby/tensorflow_c/converter.py
@@ -1,30 +1,43 @@
 # This file is useful for reading the contents of the ops generated by ruby.
 # You can read any graph defination in pb/pbtxt format generated by ruby
-# or by python and then convert it back and forth from human readable to binary format.
+# or by python and then convert it back and forth from human readable to
+# binary format.
 
 import tensorflow as tf
-import shutil, os
+import shutil
+import os
 from google.protobuf import text_format
 from tensorflow.python.platform import gfile
 
+# Converts protobuf file from pbtxt to binary wire format
+
+
 def pbtxt_to_graphdef(filename):
-  with open(filename, 'r') as f:
-    graph_def = tf.GraphDef()
-    file_content = f.read()
-    text_format.Merge(file_content, graph_def)
-    tf.import_graph_def(graph_def, name='')
-    tf.train.write_graph(graph_def, 'pbtxt/', 'protobuf.pb', as_text=False)
+    with open(filename, 'r') as f:
+        graph_def = tf.GraphDef()
+        file_content = f.read()
+        text_format.Merge(file_content, graph_def)
+        tf.import_graph_def(graph_def, name='')
+        tf.train.write_graph(graph_def, 'pbtxt/', 'protobuf.pb', as_text=False)
+
+# Converts protobuf file from binary wire format to pbtxt
+
 
 def graphdef_to_pbtxt(filename):
-  with gfile.FastGFile(filename,'rb') as f:
-    graph_defe = tf.GraphDef()
-    graph_defe.ParseFromString(f.read())
-    tf.import_graph_def(graph_defe, name='')
-#    tf.summary.FileWriter('/home/arafat/Desktop/test', graph_def = graph_defe)
-    tf.train.write_graph(graph_defe, 'pbtxt/', 'protobuf.pbtxt', as_text=True)
-  return
-
-if (os.path.isdir("/home/arafat/Desktop/tensorflow/tensorflow.rb/ext/sciruby/tensorflow_c/pbtxt")):
-  shutil.rmtree("/home/arafat/Desktop/tensorflow/tensorflow.rb/ext/sciruby/tensorflow_c/pbtxt")
-graphdef_to_pbtxt('abc')  # here you can write the name of the file to be converted
-# and then a new file will be made in pbtxt directory.
+    with gfile.FastGFile(filename, 'rb') as f:
+        graph_defe = tf.GraphDef()
+        graph_defe.ParseFromString(f.read())
+        tf.import_graph_def(graph_defe, name='')
+        tf.train.write_graph(graph_defe, 'pbtxt/',
+                             'protobuf.pbtxt', as_text=True)
+    return
+
+
+# A simple check to remove the directory if its already present.
+directory = "/home/arafat/Desktop/tensorflow/tensorflow.rb/ext/sciruby/tensorflow_c/pbtxt"
+if (os.path.isdir(directory)):
+    shutil.rmtree(directory)
+
+# Name of the file to be converted
+filename = 'int64_test.pb'
+graphdef_to_pbtxt(filename)
diff --git a/ext/sciruby/tensorflow_c/files/tf_tensor_helper.cc b/ext/sciruby/tensorflow_c/files/tf_tensor_helper.cc
@@ -219,60 +219,10 @@ std::vector<TF_Tensor *> Session_run(TF_Session* graph_session, std::vector<TF_O
         std::vector<TF_Tensor *> TF_Tensor_vector;
         for (auto i = 0; i < array_length; ++i)
                 TF_Tensor_vector.push_back(outputValues_array[i]);
-        std::cout << TF_TensorType(TF_Tensor_vector[0]) << "<- This is my type\n";
-
-
-        return TF_Tensor_vector;
-};
-
-std::vector<TF_Tensor *> Session_run_2(TF_Session* graph_session, std::vector<TF_Output > inputPorts, std::vector<TF_Tensor *> inputValues, std::vector<TF_Output > outputPorts, std::vector<TF_Operation *> cTargets)
-{
-        auto status = TF_NewStatus();
-
-        auto array_length = inputPorts.size();
-        static TF_Output *inputPorts_array;
-        inputPorts_array = new TF_Output [array_length];
-        for (auto i = 0; i < array_length; ++i)
-                inputPorts_array[i] = inputPorts[i];
-
-        array_length = outputPorts.size();
-        static TF_Output *outputPorts_array;
-        outputPorts_array = new TF_Output [array_length];
-        for (auto i = 0; i < array_length; ++i)
-                outputPorts_array[i] = outputPorts[i];
-
-        array_length = inputValues.size();
-        static TF_Tensor **inputValues_array;
-        inputValues_array = new TF_Tensor* [array_length];
-        for (auto i = 0; i < array_length; ++i)
-                inputValues_array[i] = inputValues[i];
-
-        static TF_Tensor **outputValues_array;
-        outputValues_array = new TF_Tensor* [array_length];
-
-        array_length = cTargets.size();
-        static TF_Operation **cTargets_array;
-        cTargets_array = new TF_Operation* [array_length];
-        for (auto i = 0; i < array_length; ++i)
-                cTargets_array[i] = cTargets[i];
-
-        TF_SessionRun(graph_session, NULL, &inputPorts_array[0], &inputValues_array[0], inputPorts.size(), &outputPorts_array[0], &outputValues_array[0], outputPorts.size(), &cTargets_array[0], cTargets.size(), NULL, status);
-
-        array_length = outputPorts.size();
-        std::vector<TF_Tensor *> TF_Tensor_vector;
-        for (auto i = 0; i < array_length; ++i)
-                TF_Tensor_vector.push_back(outputValues_array[i]);
-        std::cout << array_length << "<- This is array length\n";
-        long long total_elements = tensor_size(TF_Tensor_vector[0]);
-        std::cout << total_elements << "<- This is array laps\n";
-        std::cout << TF_TensorType(TF_Tensor_vector[0]) << "<- This is my type\n";
-
-
 
         return TF_Tensor_vector;
 };
 
-
 TF_Tensor** TF_Tensor_array_from_given_length(int length)
 {
         static TF_Tensor **TF_Tensor_array;

diff --git a/ext/sciruby/tensorflow_c/mysore_palace.jpg b/ext/sciruby/tensorflow_c/mysore_palace.jpg
diff --git a/lib/tensorflow/graph.rb b/lib/tensorflow/graph.rb
@@ -88,7 +88,7 @@ def const(name, value)
     # everything uptil set attributes is okay but then we need reflect equivalent for ruby
     def AddOperation(opspec)
         opspec.name = opspec.type if opspec.name.nil?
-        opspec.name = opspec.type if opspec.name == ""
+        opspec.name = opspec.type if opspec.name == ''
         cname = CString(opspec.name)
         ctype = CString(opspec.type)
         cdesc = Tensorflow::TF_NewOperation(c, ctype, cname)
@@ -99,13 +99,13 @@ def AddOperation(opspec)
             end
         end
 
-                unless opspec.inputlist.empty?
-                    c_array = Tensorflow::TF_Output_vector.new
-                    length = opspec.inputlist.length
-                    opspec.inputlist.each_with_index { |value, i| c_array[i] = value.c }
-                    c_array = Tensorflow::TF_Output_array_from_vector(c_array)
-                    cdesc = Tensorflow::input_list_helper(cdesc, c_array, length)
-                end
+        unless opspec.inputlist.empty?
+            c_array = Tensorflow::TF_Output_vector.new
+            length = opspec.inputlist.length
+            opspec.inputlist.each_with_index { |value, i| c_array[i] = value.c }
+            c_array = Tensorflow::TF_Output_array_from_vector(c_array)
+            cdesc = Tensorflow.input_list_helper(cdesc, c_array, length)
+         end
 
         status = Tensorflow::Status.new
         opspec.attr.each do |name, value|
@@ -122,15 +122,13 @@ def AddOperation(opspec)
         Tensorflow::Operation.new(Tensorflow::TF_FinishOperation(cdesc, status.c), self)
     end
 
-    # How are we using a way to set attributes for string and other types.
-    def setattr(cdesc, status, name, value) # adding extra type for fun
+    def setattr(cdesc, status, name, value)
         cAttrName = CString(name)
         type = 'DataType'      if name == 'dtype'
         type = 'Tensor'        if name == 'value'
-        type = 'int64'       if name == 'channels'
+        type = 'int64' if name == 'channels'
         type = 'DataType'      if name == 'DstT'
         type = 'int32_array'   if name == 'size/Const'
-       # print name, "  ", value, "\n\n"
         case type
         when 'string'
             Tensorflow::TF_SetAttrString(cdesc, cAttrName, CString(value), value.length)
@@ -177,7 +175,7 @@ def setattr(cdesc, status, name, value) # adding extra type for fun
             Tensorflow::TF_SetAttrTensor(cdesc, cAttrName, value.tensor, status.c)
         # TODO: Insert Tensor_list, DataType_list, Bool
         else
-            puts 'This is not working out.'
+            puts 'Attribute type not supported.'
         end
         # Shapes can be done, but will require that it be
         # distinguishable from []int64. Which is fine, it

diff --git a/lib/tensorflow/op.rb b/lib/tensorflow/op.rb
@@ -1,9 +1,8 @@
 # Const adds an operation to graph that produces value as output.
 def Const(scope, value, type = nil)
-   value = Tensorflow::Tensor.new(value, type)
-   puts value, value.type_num
-   opspec = Tensorflow::OpSpec.new("", 'Const', 'dtype' => value.type_num, 'value' => value)
-   return scope.AddOperation(opspec).output(0)
+    value = Tensorflow::Tensor.new(value, type)
+    opspec = Tensorflow::OpSpec.new('', 'Const', 'dtype' => value.type_num, 'value' => value)
+    scope.AddOperation(opspec).output(0)
 end
 
 # A placeholder op for a value that will be fed into the computation.
@@ -17,9 +16,9 @@ def Const(scope, value, type = nil)
 #
 # Returns A placeholder tensor that must be replaced using the feed mechanism.
 def Placeholder(scope, dtype, optionalAttr = nil)
-   optionalAttr = {}
-   optionalAttr["dtype"] = dtype
-   # TODO: add checks for additional attributes
-   opspec = Tensorflow::OpSpec.new("", 'Placeholder', 'dtype' => dtype)
-   return scope.AddOperation(opspec).output(0)
+    optionalAttr = {}
+    optionalAttr['dtype'] = dtype
+    # TODO: add checks for additional attributes
+    opspec = Tensorflow::OpSpec.new('', 'Placeholder', 'dtype' => dtype)
+    scope.AddOperation(opspec).output(0)
 end
diff --git a/lib/tensorflow/operation.rb b/lib/tensorflow/operation.rb
@@ -1,65 +1,65 @@
 class Tensorflow::Output
-  attr_accessor :index, :operation
-  def c
-    Tensorflow.input(operation.c, index)
-  end
+    attr_accessor :index, :operation
+    def c
+        Tensorflow.input(operation.c, index)
+    end
 
-  def dataType
-   Tensorflow::TF_OperationOutputType(c())
-  end
+    def dataType
+        Tensorflow::TF_OperationOutputType(c)
+    end
 end
 
 # Operation that has been added to the graph.
 class Tensorflow::Operation
-  attr_accessor :c, :g
-  # @!attribute c
-  #  contains the graph representation.
-  # @!attribute g
-  # A reference to the Graph to prevent it from being GCed while the Operation is still alive.
+    attr_accessor :c, :g
+    # @!attribute c
+    #  contains the graph representation.
+    # @!attribute g
+    # A reference to the Graph to prevent it from being GCed while the Operation is still alive.
 
-  def initialize(c_representation, graph)
-    self.c = c_representation
-    self.g = graph
-  end
+    def initialize(c_representation, graph)
+        self.c = c_representation
+        self.g = graph
+    end
 
-  def name
-    # May need to convert this to a ruby string
-    Tensorflow::TF_OperationName(self.c)
-  end
+    def name
+        # May need to convert this to a ruby string
+        Tensorflow::TF_OperationName(c)
+    end
 
-  def type
-    # May need to convert this to a ruby string
-    Tensorflow::TF_OperationOpType(self.c)
-  end
+    def type
+        # May need to convert this to a ruby string
+        Tensorflow::TF_OperationOpType(c)
+    end
 
-  def num_outputs
-    # May need to convert this to ruby int
-    Tensorflow::TF_OperationNumOutputs(self.c)
-  end
+    def num_outputs
+        # May need to convert this to ruby int
+        Tensorflow::TF_OperationNumOutputs(c)
+    end
 
-  # OutputListSize returns the size of the list of Outputs that is produced by a
-  # named output of op.
-  #
-  # An Operation has multiple named outputs, each of which produces either
-  # a single tensor or a list of tensors. This method returns the size of
-  # the list of tensors for a specific output of the operation, identified
-  # by its name.
-  def output_list_size(output)
-    cname = CString(output)
-    status = Tensorflow::Status.new
-    Tensorflow::TF_OperationOutputListLength(self.c, cname, status.c)
-  end
+    # OutputListSize returns the size of the list of Outputs that is produced by a
+    # named output of op.
+    #
+    # An Operation has multiple named outputs, each of which produces either
+    # a single tensor or a list of tensors. This method returns the size of
+    # the list of tensors for a specific output of the operation, identified
+    # by its name.
+    def output_list_size(output)
+        cname = CString(output)
+        status = Tensorflow::Status.new
+        Tensorflow::TF_OperationOutputListLength(c, cname, status.c)
+    end
 
-  def output(i)
-    out = Tensorflow::Output.new
-    out.operation = self
-    out.index = i
-    out
-  end
+    def output(i)
+        out = Tensorflow::Output.new
+        out.operation = self
+        out.index = i
+        out
+    end
 end
 
 class Tensorflow::Input
-  attr_accessor :Index, :Operations
-  def initialize
-  end
+    attr_accessor :Index, :Operations
+    def initialize
+    end
 end