def _create_var(name, value):
dtype = plaidml.DType.from_numpy(value.dtype)
shape = edsl.LogicalShape(dtype, value.shape)
tensor_shape = plaidml.TensorShape(dtype, value.shape)
buffer = plaidml.Buffer(_device, tensor_shape)
buffer.copy_from_ndarray(value)
return edsl.Tensor(shape=shape, name=name, buffer=buffer)
def _get_buffer(self, map, arg):
buffer = map.get(arg.ref)
if buffer:
return buffer
buffer = plaidml.Buffer(arg.shape.into_TensorShape(), device=self.device)
map[arg.ref] = buffer
return buffer
def make_buffer(tensor):
# convert LogicalShape into TensorShape
shape = plaidml.TensorShape(tensor.shape.dtype, tensor.shape.int_dims)
return plaidml.Buffer(_device, shape)
def make_buffer(tensor):
# convert LogicalShape into TensorShape
return plaidml.Buffer(device, tensor.shape.into_TensorShape())
def set_value(x, value):
dtype = plaidml.DType.from_numpy(value.dtype)
tensor_shape = plaidml.TensorShape(dtype, value.shape)
buffer = plaidml.Buffer(_device, tensor_shape)
buffer.copy_from_ndarray(value)
x.tensor.set_param_value(buffer)
