init mnist #3564
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init mnist #3564
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wangkuiyi
reviewed
Aug 22, 2017
| return cost_name | ||
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| def get_backward_net(forward_net): |
| return net | ||
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| def print_inputs_outputs(op): |
dzhwinter
reviewed
Aug 23, 2017
| var = scope.new_var(param_name) | ||
| tensor = var.get_tensor() | ||
| tensor.set_dims(dims) | ||
| data = numpy.random.uniform( |
Contributor
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as a demo, maybe we better use the built-in operator?
dzhwinter
reviewed
Aug 24, 2017
| cost_grad.set(numpy.ones(cost_shape).astype("float32"), place) | ||
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| def mean_cost(cost): |
Contributor
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mean cost get the cross_entropy output for debugging. we'd better rename this snippet.
dzhwinter
approved these changes
Aug 24, 2017
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fix: #3557 use low level API to construct a mnist training logic
sgd-op[done] 8b3d33arowwiseadd-grad-op[done] "add rowwise add backward op" #3183 82b820emul-grad-op[done] "mul op gradient" #3379math matmul[done] fix math matmul #3577rowwiseadd-grad-op[done] Fix rowwise add #3604rowwise_grad_gpu_op[done] register rowwise add gpu kernel #3660