Sourcery Starbot ⭐ refactored manncodes/xeno #1
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| def derivative(self, input=None): | ||
| last_forward = input if input else self.last_forward | ||
| last_forward = input or self.last_forward |
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Function ReLU.derivative refactored with the following changes:
- Simplify if expression by using or (
or-if-exp-identity)
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| def derivative(self, input=None): | ||
| last_forward = input if input else self.last_forward | ||
| last_forward = input or self.last_forward |
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Function Linear.derivative refactored with the following changes:
- Simplify if expression by using or (
or-if-exp-identity)
| exp_x = np.exp(x) | ||
| s = exp_x / np.sum(exp_x, axis=1, keepdims=True) | ||
| return s | ||
| return exp_x / np.sum(exp_x, axis=1, keepdims=True) |
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Function Softmax.forward refactored with the following changes:
- Inline variable that is immediately returned (
inline-immediately-returned-variable)
| last_forward = input if input else self.last_forward | ||
| last_forward = input or self.last_forward |
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Function Softmax.derivative refactored with the following changes:
- Simplify if expression by using or (
or-if-exp-identity)
| fan_out = size[1] | ||
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| elif len(size) == 4 or len(size) == 5: | ||
| elif len(size) in [4, 5]: |
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Function decompose_size refactored with the following changes:
- Replace multiple comparisons of same variable with
inoperator (merge-comparisons)
| while iter_idx < max_iter: | ||
| iter_idx += 1 | ||
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| for iter_idx in range(1, max_iter + 1): |
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Function Model.fit refactored with the following changes:
- Replace while with for (
while-to-for)
| y_pred = x_next | ||
| return y_pred | ||
| return x_next |
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Function Model.predict refactored with the following changes:
- Inline variable that is immediately returned (
inline-immediately-returned-variable)
| linear_out = np.dot(input, self.W) + self.b | ||
| act_out = self.act_layer.forward(linear_out) | ||
| return act_out | ||
| return self.act_layer.forward(linear_out) |
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Function Dense.forward refactored with the following changes:
- Inline variable that is immediately returned (
inline-immediately-returned-variable)
| if train: | ||
| self.last_mask = get_rng().binomial(1, 1 - self.p, input.shape) / (1 - self.p) | ||
| return input * self.last_mask | ||
| else: | ||
| if not train: | ||
| return input * (1 - self.p) | ||
| self.last_mask = get_rng().binomial(1, 1 - self.p, input.shape) / (1 - self.p) | ||
| return input * self.last_mask |
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Function Dropout.forward refactored with the following changes:
- Swap if/else branches (
swap-if-else-branches) - Remove unnecessary else after guard condition (
remove-unnecessary-else)
| dx = dx1 + dx2 | ||
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| return dx | ||
| return dx1 + dx2 |
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Function BatchNormal.backward refactored with the following changes:
- Inline variable that is immediately returned (
inline-immediately-returned-variable)
This removes the following comments ( why? ):
# step0 done!
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