Neural Network
Artificial neural networks (ANN) are computational systems that "learn" to perform tasks by considering examples, generally without being programmed with any task-specific rules.
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🚀 The feature, motivation and pitch
After the revert of pytorch/pytorch@7cf9b94 we've identified a need to add a lint that checks file names to ensure that they're compatible with Windows machines.
Observed error: (from example commit)
Error: error: invalid path 'test/test_ops_gradients.py '
A simple check on chang
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fitDataset() expects a Dataset that produces elements of a certain shape, with matching batch sizes etc., and throws errors (from standardizeDataIteratorOutput()) when the conditions are not met. These errors should be tested.
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In gensim/models/fasttext.py:
model = FastText(
vector_size=m.dim,
vector_size=m.dim,
window=m.ws,
window=m.ws,
epochs=m.epoch,
epochs=m.epoch,
negative=m.neg,
negative=m.neg,
# FIXME: these next 2 lines read in unsupported FB FT modes (loss=3 softmax or loss=4 onevsall,
# or model=3 supervi-
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New Operator
Describe the operator
Why is this operator necessary? What does it accomplish?
This is a frequently used operator in tensorflow/keras
Can this operator be constructed using existing onnx operators?
If so, why not add it as a function?
I don't know.
Is this operator used by any model currently? Which one?
Are you willing to contribute it?
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Describe the issue:
During computing Channel Dependencies reshape_break_channel_dependency does following code to ensure that the number of input channels equals the number of output channels:
in_shape = op_node.auxiliary['in_shape']
out_shape = op_node.auxiliary['out_shape']
in_channel = in_shape[1]
out_channel = out_shape[1]
return in_channel != out_channel
This is correct
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Current implementation of Go binding can not specify options.
GPUOptions struct is in internal package. And
go generatedoesn't work for protobuf directory. So we can't specify GPUOptions forNewSession.