tensor.py

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main.py | graph.py | tensor.py | ops.py | session.py

from __future__ import absolute_import
from __future__ import print_function
from __future__ import division

import numpy as np

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Tensor represents a value in the graph. It's just a data container with methods for operator overloading (each of which delegate to the graph). It includes:

The initial value of the tensor.
The operation which produced the tensor, if applicable.
A reference to the graph this tensor belongs to.

class Tensor(object):

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    def __init__(self, initial_value, op, graph):
        self.initial_value = initial_value
        self.graph = graph
        self.op = op

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Operator Overloading

    def __add__(self, other):
        return self.graph.add(self, other)

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    def __sub__(self, other):
        return self.graph.sub(self, other)

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    def __mul__(self, other):
        return self.graph.mul(self, other)

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    def __truediv__(self, other):
        return self.graph.div(self, other)

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    def __neg__(self):
        return self.graph.neg(self)

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Reverse Operator Overloading

    def __radd__(self, other):
        return self.graph.add(other, self)

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    def __rsub__(self, other):
        return self.graph.sub(other, self)

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    def __rmul__(self, other):
        return self.graph.mul(other, self)

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    def __rtruediv__(self, other):
        return self.graph.div(other, self)