46 lines
1.1 KiB
Python
46 lines
1.1 KiB
Python
"""Module for operators vectorize implementation"""
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import torch
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from pina.label_tensor import LabelTensor
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def grad(output_, input_):
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"""
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TODO
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"""
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if not isinstance(input_, LabelTensor):
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raise TypeError
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gradients = torch.autograd.grad(
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output_,
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input_.tensor,
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grad_outputs=torch.ones(output_.size()).to(
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dtype=input_.tensor.dtype,
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device=input_.tensor.device),
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create_graph=True, retain_graph=True, allow_unused=True)[0]
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return LabelTensor(gradients, input_.labels)
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def div(output_, input_):
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"""
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TODO
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"""
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if output_.tensor.shape[1] == 1:
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div = grad(output_.tensor, input_).sum(axis=1)
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else: # really to improve
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a = []
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for o in output_.tensor.T:
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a.append(grad(o, input_).tensor)
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div = torch.zeros(output_.tensor.shape[0], 1)
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for i in range(output_.tensor.shape[1]):
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div += a[i][:, i].reshape(-1, 1)
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return div
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def nabla(output_, input_):
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"""
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TODO
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"""
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return div(grad(output_, input_), input_)
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