wehub-resource-sync
56 lines
1.6 KiB
Python
Executable File
56 lines
1.6 KiB
Python
Executable File
import numpy as np
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from prml.nn.tensor.constant import Constant
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from prml.nn.tensor.tensor import Tensor
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from prml.nn.function import Function
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class Product(Function):
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def __init__(self, axis=None, keepdims=False):
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if isinstance(axis, int):
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axis = (axis,)
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elif isinstance(axis, tuple):
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axis = tuple(sorted(axis))
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self.axis = axis
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self.keepdims = keepdims
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def forward(self, x):
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x = self._convert2tensor(x)
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self.x = x
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self.output = np.prod(self.x.value, axis=self.axis, keepdims=True)
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if not self.keepdims:
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output = np.squeeze(self.output)
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if output.size == 1:
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output = output.item()
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else:
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output = self.output
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if isinstance(self.x, Constant):
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return Constant(output)
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return Tensor(output, function=self)
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def backward(self, delta):
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if not self.keepdims and self.axis is not None:
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for ax in self.axis:
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delta = np.expand_dims(delta, ax)
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dx = delta * self.output / self.x.value
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self.x.backward(dx)
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def prod(x, axis=None, keepdims=False):
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"""
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product of all element in the array
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Parameters
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----------
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x : tensor_like
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input array
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axis : int, tuple of ints
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axis or axes along which a product is performed
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keepdims : bool
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keep dimensionality or not
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Returns
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-------
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product : tensor_like
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product of all element
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"""
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return Product(axis=axis, keepdims=keepdims).forward(x)
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