def repeat_to_match_shape(x, axis, keepdims):
"""Returns a function that repeats an array along axis to get a given shape.
Also returns the number of repetitions of the array."""
assert isinstance(axis, (type(None), int, tuple))
if not isarray(x):
return I, 1
shape = x.shape
if axis is None:
dtype=None
if anp.iscomplexobj(x):
dtype = getval(anp.array(x)).dtype # np.full() has a bug for complex numbers
if keepdims:
return lambda g : anp.full(shape, anp.sum(g), dtype=dtype), anp.prod(shape)
else:
return lambda g : anp.full(shape, g, dtype=dtype), anp.prod(shape)
elif isinstance(axis, int):
if keepdims:
return lambda g : anp.repeat(g, shape[axis], axis), shape[axis]
else:
return lambda g : anp.repeat(anp.expand_dims(g, axis),
shape[axis], axis), shape[axis]
else:
repeats = [shape[i] if i in axis else 1 for i in range(len(shape))]
expanded = [shape[i] if i not in axis else 1 for i in range(len(shape))]
num_reps = anp.prod(anp.array(shape)[list(axis)])
if keepdims:
return lambda g: anp.tile(g, repeats), num_reps
else:
return lambda g: anp.tile(anp.reshape(g, expanded), repeats), num_reps
def double_val_fun(*args, **kwargs):
val = fun(*args, **kwargs)
return val, getval(val)
def wrapped(*args, **kwargs):
unboxed_args = map(getval, args)
unboxed_kwargs = {key: getval(kwargs[key]) for key in kwargs}
return f(*unboxed_args, **unboxed_kwargs)
def sum_outgrads(outgrads):
if len(outgrads) is 1 and not isinstance(getval(outgrads[0]), SparseArray):
return outgrads[0]
else:
return primitive_sum_arrays(*outgrads)
def zeros_like(self):
return {k : zeros_like(v) for k, v in iteritems(getval(self))}
def zeros_like(value):
return [zeros_like(item) for item in getval(value)]
def make_grad_tile(ans, x, reps):
reps = [reps] if anp.isscalar(reps) else reps
def tile_grad(g):
for axis, rep in enumerate(reps):
g = sum(anp.split(g, rep, axis))
return anp.reshape(g, x.shape)
return tile_grad
anp.tile.defgrad(make_grad_tile)
def make_grad_transpose(ans, x, axes=None):
if axes is not None:
axes = anp.argsort(axes)
return lambda g : anp.transpose(g, axes)
anp.transpose.defgrad(make_grad_transpose)
isarray = lambda x : isinstance(getval(x), anp.ndarray)
def repeat_to_match_shape(x, axis, keepdims):
"""Returns a function that repeats an array along axis to get a given shape.
Also returns the number of repetitions of the array."""
assert isinstance(axis, (type(None), int, tuple))
if not isarray(x):
return I, 1
shape = x.shape
if axis is None:
dtype=None
if anp.iscomplexobj(x):
dtype = getval(anp.array(x)).dtype # np.full() has a bug for complex numbers
if keepdims:
return lambda g : anp.full(shape, anp.sum(g), dtype=dtype), anp.prod(shape)
