[Prim][PIR] group_norm decomposite rule support dynamic shape #62793
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| self.init_x_shape = [None, 640, None, None] | ||
| self.x = np.random.random(self.x_shape).astype(self.dtype) | ||
| self.net = group_norm_net1 | ||
| self.necessary_ops = "pd_op.flatten" |
cyber-pioneer
approved these changes
Mar 21, 2024
| Tensor x_shape = get_slice<T>(x_dim, 0) * groups; | ||
| Tensor dim_1 = full<T>({1}, -1, x_dim.type()); | ||
| x_shape = concat<T>({x_shape, dim_1}); | ||
| x_cast = backend::reshape<T>(x_cast, x_shape); |
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| x_cast = backend::reshape<T>(x_cast, x_shape); | |
| x_cast = reshape<T>(x_cast, x_shape); |
| Tensor dim_1 = full<T>({1}, -1, x_dim.type()); | ||
| x_shape = concat<T>({x_shape, dim_1}); | ||
| x_cast = backend::reshape<T>(x_cast, x_shape); | ||
| mean_ = mean_decomp<T>(x_cast, IntArray(one_axis), true); |
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Description
support dynamic shape for group_norm