README.md in tensor_stream-0.1.3 vs README.md in tensor_stream-0.1.4
- old
+ new
@@ -1,5 +1,7 @@
+[](https://badge.fury.io/rb/tensor_stream)
+
# TensorStream
A reimplementation of TensorFlow for ruby. This is a ground up implementation with no dependency on TensorFlow. Effort has been made to make the programming style as near to TensorFlow as possible, comes with a pure ruby evaluator by default as well with support for an opencl evaluator.
The goal of this gem is to have a high performance machine learning and compute solution for ruby with support for a wide range of hardware and software configuration.
@@ -92,12 +94,16 @@
puts("Training cost=", training_cost, "W=", sess.run(W), "b=", sess.run(b), '\n')
puts("time elapsed ", Time.now.to_i - start_time.to_i)
end
```
-## python to ruby guide
+You can take a look at spec/tensor_stream/operation_spec.rb for a list of supported ops and various examples and test cases used. Of course these contain only a
+sliver of what TensorFlow can do, so feel free to file a PR to add requested
+ops and test cases.
+## Python to Ruby guide
+
Not all ops are available. Available ops are defined in lib/tensor_stream/ops.rb, corresponding gradients are found at lib/tensor_stream/math_gradients.
There are also certain differences with regards to naming conventions, and named parameters:
# Variables
@@ -120,11 +126,11 @@
```
Ruby
```ruby
-w =tf.variable(0, name: 'weights')
+w = tf.variable(0, name: 'weights')
```
# Shapes
Python
@@ -148,10 +154,10 @@
Y = tf.placeholder("float")
W = tf.variable(rand, name: "weight")
b = tf.variable(rand, name: "bias")
pred = X * W + b
cost = tf.reduce_sum(tf.pow(pred - Y, 2)) / ( 2 * 10)
-cost.to_math # "(reduce_sum(|((((Placeholder: * weight) + bias) - Placeholder_2:)^2)|) / 10.0)"
+cost.to_math # "(reduce_sum(|((((Placeholder: * weight) + bias) - Placeholder_2:)^2)|) / 20.0)"
```
breakpoints can also be set, block will be evaluated during computation
```ruby