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miaobytemiaobyte
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linear:linear验证
1 parent 184c4b7 commit 0ec68c1

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Lines changed: 219 additions & 268 deletions

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‎front/py/deepx/nn/functional/__init__.py‎

Lines changed: 1 addition & 1 deletion
Original file line numberDiff line numberDiff line change
@@ -10,7 +10,7 @@
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__all__ = [
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"newtensor",
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"printtensor",
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"constant","full","zeros","ones","uniform","arange","rand","randn","eye","kaiming_uniform_",
13+
"constant","full","zeros","ones","uniform","arange","rand","randn","eye","kaiming_uniform_","calculate_fan_in_and_fan_out",
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"add","sub","mul","div","clamp","exp","sqrt","rsqrt",
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"matmul",
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"max","min","sum","prod","mean",

‎front/py/deepx/nn/functional/init.py‎

Lines changed: 2 additions & 2 deletions
Original file line numberDiff line numberDiff line change
@@ -72,7 +72,7 @@ def eye(
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pass
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def _calculate_fan_in_and_fan_out(tensor:Tensor):
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def calculate_fan_in_and_fan_out(tensor:Tensor):
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dimensions = tensor.dim()
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if dimensions < 2:
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raise ValueError(
@@ -98,7 +98,7 @@ def _calculate_correct_fan(tensor:Tensor, mode:str):
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if mode not in valid_modes:
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raise ValueError(f"Mode {mode} not supported, please use one of {valid_modes}")
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101-
fan_in, fan_out = _calculate_fan_in_and_fan_out(tensor)
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fan_in, fan_out = calculate_fan_in_and_fan_out(tensor)
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return fan_in if mode == "fan_in" else fan_out
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104104
#copy from torch.nn/init.py

‎front/py/deepx/nn/modules/linear.py‎

Lines changed: 11 additions & 6 deletions
Original file line numberDiff line numberDiff line change
@@ -1,6 +1,7 @@
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from .module import Module
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from deepx.tensor import Tensor
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from deepx import Tensor
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from deepx.nn.functional import uniform,kaiming_uniform_,calculate_fan_in_and_fan_out
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import math
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class Linear(Module):
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r'''
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copy from torch.nn.Linear
@@ -30,14 +31,18 @@ def reset_parameters(self) -> None:
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# Setting a=sqrt(5) in kaiming_uniform is the same as initializing with
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# uniform(-1/sqrt(in_features), 1/sqrt(in_features)). For details, see
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# https://github.com/pytorch/pytorch/issues/57109
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init.kaiming_uniform_(self.weight, a=math.sqrt(5))
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kaiming_uniform_(self.weight, a=math.sqrt(5))
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if self.bias is not None:
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fan_in, _ = init._calculate_fan_in_and_fan_out(self.weight)
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fan_in, _ = calculate_fan_in_and_fan_out(self.weight)
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bound = 1 / math.sqrt(fan_in) if fan_in > 0 else 0
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init.uniform_(self.bias, -bound, bound)
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uniform(self.bias, -bound, bound)
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def forward(self, input: Tensor) -> Tensor:
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return F.linear(input, self.weight, self.bias)
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#`y = xA^T + b`
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if self.bias is None:
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return input @ self.weight.T
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else:
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return input @ self.weight.T + self.bias
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def extra_repr(self) -> str:
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return f"in_features={self.in_features}, out_features={self.out_features}, bias={self.bias is not None}"

‎front/py/examples/3_module/1_linear.py‎

Lines changed: 2 additions & 10 deletions
Original file line numberDiff line numberDiff line change
@@ -1,18 +1,10 @@
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from deepx.nn.modules import Linear, Module
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from deepx import Tensor
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class Net(Module):
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def __init__(self):
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super().__init__()
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self.fc1 = Linear(64, 32)
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self.fc2 = Linear(32, 2)
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def forward(self, x):
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x = self.fc1(x)
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x = self.fc2(x)
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return x
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net = Net()
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net = Linear(64, 4)
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input=Tensor(shape=[1,64])
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out=net.forward(input)
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print(out)
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net.graph.to_dot().render('linear.dot',format='svg')
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for name, param in net.named_parameters():

‎front/py/examples/3_module/linear.dot‎

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digraph {
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rankdir=TB
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}

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