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| require 'tensorflow' | |
| graph = Tensorflow::Graph.new | |
| tensor_1 = Tensorflow::Tensor.new([[2, 2.3], [ 10, 6.2]]) | |
| tensor_2 = Tensorflow::Tensor.new([[4, 3.2], [ 47, 1.2]]) | |
| placeholder_1 = graph.placeholder('tensor1', tensor_1.type_num) | |
| placeholder_2 = graph.placeholder('tensor2', tensor_2.type_num) | |
| opspec = Tensorflow::OpSpec.new('Addition_of_tensors', 'Add', nil, [placeholder_1, placeholder_2]) | |
| op = graph.AddOperation(opspec) | |
| session_op = Tensorflow::Session_options.new | |
| session = Tensorflow::Session.new(graph, session_op) | |
| hash = {} | |
| hash[placeholder_1] = tensor_1 | |
| hash[placeholder_2] = tensor_2 | |
| result = session.run(hash, [op.output(0)], []) | |
| print result[0], "\n" |
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Yeah, definitely not the empty
()parenthesis if not parameters.Regarding using symbols instead of strings, we need to be careful initially, because TensorFlow complains if we pass it a
Symbolas the key. So at some point we should convert any placeholder names/keys toStringbefore passing them on to TensorFlow and maybe useHashWithIndifferentAccesswhen a tensor is fetched from TensorFlow.