Differences with torch.nn.GRUCell

torch.nn.GRUCell

class torch.nn.GRUCell(
    input_size,
    hidden_size,
    bias=True)(input, hidden) -> Tensor

For more information, see torch.nn.GRUCell.

mindspore.nn.GRUCell

class mindspore.nn.GRUCell(
    input_size: int,
    hidden_size: int,
    has_bias: bool=True)(x, hx) -> Tensor

For more information, see mindspore.nn.GRUCell.

Differences

PyTorch: Recurrent Neural Network unit.

MindSpore: MindSpore API implements the same functions as PyTorch.

Categories	Subcategories	PyTorch	MindSpore	Difference
Parameters	Parameter 1	input_size	input_size	-
	Parameter 2	hidden_size	hidden_size	-
	Parameter 3	bias	has_bias	Same function, different parameter names
Inputs	Input 1	input	x	Same function, different parameter names
	Input 2	hidden	hx	Same function, different parameter names

Code Example 1

# PyTorch
import torch
from torch import tensor
import numpy as np

grucell = torch.nn.GRUCell(2, 3, bias=False)
input = torch.tensor(np.array([[3.0, 4.0]]).astype(np.float32))
hidden = torch.tensor(np.array([[1.0, 2.0, 3]]).astype(np.float32))
output = grucell(input, hidden)
print(output)
# tensor([[ 0.9948,  0.0913, -0.1633]], grad_fn=<AddBackward0>)

# MindSpore
import mindspore.nn as nn
from mindspore import Tensor
import numpy as np

grucell = nn.GRUCell(2, 3, has_bias=False)
x = Tensor(np.array([[3.0, 4.0]]).astype(np.float32))
hx = Tensor(np.array([[1.0, 2.0, 3]]).astype(np.float32))
output = grucell(x, hx)
print(output)
# [[-0.94861907  0.6191679   2.1289415 ]]