| @@ -15,7 +15,6 @@ | |||||
| """math""" | """math""" | ||||
| import math | import math | ||||
| import numpy as np | import numpy as np | ||||
| import mindspore.context as context | |||||
| from mindspore.ops import operations as P | from mindspore.ops import operations as P | ||||
| from mindspore.ops.operations import _inner_ops as inner | from mindspore.ops.operations import _inner_ops as inner | ||||
| from mindspore.common.tensor import Tensor | from mindspore.common.tensor import Tensor | ||||
| @@ -128,7 +127,6 @@ class Range(Cell): | |||||
| def __init__(self, start, limit=None, delta=1): | def __init__(self, start, limit=None, delta=1): | ||||
| super(Range, self).__init__() | super(Range, self).__init__() | ||||
| self.is_gpu = context.get_context("device_target") == "GPU" | |||||
| validator.check_value_type("start", start, [int, float], self.cls_name) | validator.check_value_type("start", start, [int, float], self.cls_name) | ||||
| validator.check_value_type("delta", delta, [int, float], self.cls_name) | validator.check_value_type("delta", delta, [int, float], self.cls_name) | ||||
| if delta == 0: | if delta == 0: | ||||
| @@ -157,17 +155,8 @@ class Range(Cell): | |||||
| length_input = math.ceil((limit - start) / delta) | length_input = math.ceil((limit - start) / delta) | ||||
| self.input_tensor = Tensor(list(range(length_input)), self.dtype) | self.input_tensor = Tensor(list(range(length_input)), self.dtype) | ||||
| if self.is_gpu: | |||||
| self.start = Tensor(start, self.dtype) | |||||
| self.limit = Tensor(limit, self.dtype) | |||||
| self.delta = Tensor(delta, self.dtype) | |||||
| self.range_gpu = P.Range(length_input) | |||||
| def construct(self): | def construct(self): | ||||
| if self.is_gpu: | |||||
| range_out = self.range_gpu(self.start, self.limit, self.delta) | |||||
| else: | |||||
| range_out = self.range_x(self.input_tensor) | |||||
| range_out = self.range_x(self.input_tensor) | |||||
| return range_out | return range_out | ||||