def __init__(self, inputs, outputs, **kwargs):
if not isinstance(outputs, list):
raise TypeError("outputs must be list", outputs)
for i in inputs + outputs:
if not isinstance(i, gof.Variable):
raise TypeError("inputs and outputs must be Variable instances", i)
if "updates" in kwargs or "givens" in kwargs:
raise TypeError("updates and givens are not allowed in kwargs")
# To support correctly shared variables the inner fct should
# not see them. Otherwise their is problem with the gradient.
self.shared_inputs = [var for var in gof.graph.inputs(outputs) if isinstance(var, SharedVariable)]
shared_vars = [var.type() for var in self.shared_inputs]
new = rebuild_collect_shared(
outputs,
inputs=inputs + shared_vars,
replace=dict(izip(self.shared_inputs, shared_vars)),
copy_inputs_over=False,
)
(new_inputs, new_outputs, [clone_d, update_d, update_expr, shared_inputs]) = new
assert len(new_inputs) == len(inputs) + len(self.shared_inputs)
assert len(new_outputs) == len(outputs)
assert not update_d
assert not update_expr
assert not shared_inputs
self.new_inputs = new_inputs
self.new_outputs = new_outputs
self.inputs = inputs
self.outputs = outputs
self.kwargs = kwargs
self.input_types = [input.type for input in inputs]
self.output_types = [output.type for output in outputs]
def __init__(self, inputs, outputs, **kwargs):
if not isinstance(outputs, list):
raise TypeError('outputs must be list', outputs)
for i in inputs + outputs:
if not isinstance(i, gof.Variable):
raise TypeError(
'inputs and outputs must be Variable instances', i)
if 'updates' in kwargs:
raise TypeError('updates are not allowed in kwargs')
# To support correctly shared variables the inner fct should
# not see them. Otherwise their is problem with the gradient.
self.shared_inputs = [var for var in gof.graph.inputs(outputs)
if isinstance(var, SharedVariable)]
shared_vars = [var.type() for var in self.shared_inputs]
new = rebuild_collect_shared(outputs, inputs=inputs + shared_vars,
replace=dict(zip(self.shared_inputs,
shared_vars)),
copy_inputs_over=False)
(new_inputs, new_outputs,
[clone_d, update_d, update_expr, shared_inputs]) = new
assert len(new_inputs) == len(inputs) + len(self.shared_inputs)
assert len(new_outputs) == len(outputs)
assert not update_d
assert not update_expr
assert not shared_inputs
self.new_inputs = new_inputs
self.new_outputs = new_outputs
self.inputs = inputs
self.outputs = outputs
self.kwargs = kwargs
self.input_types = [input.type for input in inputs]
self.output_types = [output.type for output in outputs]
def __init__(
self, inputs, outputs,
inline=False,
lop_overrides='default',
grad_overrides='default',
rop_overrides='default',
name=None, **kwargs
):
if not isinstance(outputs, list):
raise TypeError('outputs must be list, got %s' % type(outputs))
for i in inputs + outputs:
if not isinstance(i, gof.Variable):
raise TypeError(
'inputs and outputs must be Variable instances', i)
if 'updates' in kwargs or 'givens' in kwargs:
raise TypeError('updates and givens are not allowed here')
self.is_inline = inline
# To correctly support shared variables the inner fct should
# not see them. Otherwise there is a problem with the gradient.
self.shared_inputs = [var for var in gof.graph.inputs(outputs)
if isinstance(var, SharedVariable)]
shared_vars = [var.type() for var in self.shared_inputs]
new = rebuild_collect_shared(outputs, inputs=inputs + shared_vars,
replace=dict(izip(
self.shared_inputs, shared_vars)),
copy_inputs_over=False)
(local_inputs, local_outputs,
[clone_d, update_d, update_expr, shared_inputs]) = new
assert len(local_inputs) == len(inputs) + len(self.shared_inputs)
assert len(local_outputs) == len(outputs)
assert not update_d
assert not update_expr
assert not shared_inputs
self.local_inputs = local_inputs
self.local_outputs = local_outputs
self.inputs = inputs
self.outputs = outputs
self.kwargs = kwargs
self.input_types = [inp.type for inp in inputs]
self.output_types = [out.type for out in outputs]
if lop_overrides != 'default':
if grad_overrides != 'default':
raise ValueError('lop_overrides and grad_overrides are mutually exclusive')
else:
self.set_lop_overrides(lop_overrides)
self._lop_type = 'lop'
elif grad_overrides != 'default':
self.set_lop_overrides(grad_overrides)
self._lop_type = 'grad'
else:
self.set_lop_overrides('default')
self._lop_type = 'lop'
self.set_rop_overrides(rop_overrides)
if name is not None:
assert isinstance(name, str), 'name must be None or string object'
self.name = name
def __init__(self,
inputs,
outputs,
inline=False,
grad_overrides='default',
rop_overrides='default',
name=None,
**kwargs):
if not isinstance(outputs, list):
raise TypeError('outputs must be list, got %s' % type(outputs))
for i in inputs + outputs:
if not isinstance(i, gof.Variable):
raise TypeError(
'inputs and outputs must be Variable instances', i)
if 'updates' in kwargs or 'givens' in kwargs:
raise TypeError('updates and givens are not allowed here')
self.is_inline = inline
# To correctly support shared variables the inner fct should
# not see them. Otherwise there is a problem with the gradient.
self.shared_inputs = [
var for var in gof.graph.inputs(outputs)
if isinstance(var, SharedVariable)
]
shared_vars = [var.type() for var in self.shared_inputs]
new = rebuild_collect_shared(outputs,
inputs=inputs + shared_vars,
replace=dict(
izip(self.shared_inputs,
shared_vars)),
copy_inputs_over=False)
(local_inputs, local_outputs,
[clone_d, update_d, update_expr, shared_inputs]) = new
assert len(local_inputs) == len(inputs) + len(self.shared_inputs)
assert len(local_outputs) == len(outputs)
assert not update_d
assert not update_expr
assert not shared_inputs
self.local_inputs = local_inputs
self.local_outputs = local_outputs
self.inputs = inputs
self.outputs = outputs
self.kwargs = kwargs
self.input_types = [inp.type for inp in inputs]
self.output_types = [out.type for out in outputs]
self.set_grad_overrides(grad_overrides)
self.set_rop_overrides(rop_overrides)
if name is not None:
assert isinstance(name, str), 'name must be None or string object'
self.name = name
def __init__(
self,
inputs,
outputs,
inline=False,
lop_overrides="default",
grad_overrides="default",
rop_overrides="default",
connection_pattern=None,
name=None,
**kwargs,
):
if not isinstance(outputs, list):
raise TypeError("outputs must be list, got %s" % type(outputs))
for i in inputs + outputs:
if not isinstance(i, gof.Variable):
raise TypeError(
"inputs and outputs must be Variable instances", i)
if "updates" in kwargs or "givens" in kwargs:
raise TypeError("updates and givens are not allowed here")
self.is_inline = inline
# To correctly support shared variables the inner fct should
# not see them. Otherwise there is a problem with the gradient.
self.shared_inputs = [
var for var in gof.graph.inputs(outputs)
if isinstance(var, SharedVariable)
]
shared_vars = [var.type() for var in self.shared_inputs]
new = rebuild_collect_shared(
outputs,
inputs=inputs + shared_vars,
replace=dict(zip(self.shared_inputs, shared_vars)),
copy_inputs_over=False,
)
(
local_inputs,
local_outputs,
[clone_d, update_d, update_expr, shared_inputs],
) = new
assert len(local_inputs) == len(inputs) + len(self.shared_inputs)
assert len(local_outputs) == len(outputs)
assert not update_d
assert not update_expr
assert not shared_inputs
self.local_inputs = local_inputs
self.local_outputs = local_outputs
self.inputs = inputs
self.outputs = outputs
self.kwargs = kwargs
self.input_types = [inp.type for inp in inputs]
self.output_types = [out.type for out in outputs]
if lop_overrides != "default":
if grad_overrides != "default":
raise ValueError(
"lop_overrides and grad_overrides are mutually exclusive")
else:
self.set_lop_overrides(lop_overrides)
self._lop_type = "lop"
elif grad_overrides != "default":
self.set_lop_overrides(grad_overrides)
self._lop_type = "grad"
else:
self.set_lop_overrides("default")
self._lop_type = "lop"
self.set_rop_overrides(rop_overrides)
self._connection_pattern = connection_pattern
if name is not None:
assert isinstance(name, str), "name must be None or string object"
self.name = name
