mirror of https://github.com/commaai/tinygrad.git
moving `mask_like` to utils
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@ -1,4 +1,6 @@
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import numpy as np
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from tinygrad.utils import mask_like
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from tinygrad.tensor import Tensor
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def jacobian(func, input):
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@ -18,11 +20,6 @@ def jacobian(func, input):
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J[o,i] = grad
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return J
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def mask_like(like, mask_inx, mask_value = 1.0):
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mask = np.zeros_like(like).reshape(-1)
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mask[mask_inx] = mask_value
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return mask.reshape(like.shape)
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def numerical_jacobian(func, input, eps = 1e-6):
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output = func(input)
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@ -45,5 +42,4 @@ def numerical_jacobian(func, input, eps = 1e-6):
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def gradcheck(func, input, eps = 1e-06, atol = 1e-5, rtol = 0.001):
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NJ = numerical_jacobian(func, input, eps)
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J = jacobian(func, input)
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return np.allclose(J, NJ, atol=atol, rtol=rtol)
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@ -1,5 +1,10 @@
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import numpy as np
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def mask_like(like, mask_inx, mask_value = 1.0):
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mask = np.zeros_like(like).reshape(-1)
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mask[mask_inx] = mask_value
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return mask.reshape(like.shape)
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def layer_init_uniform(*x):
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ret = np.random.uniform(-1., 1., size=x)/np.sqrt(np.prod(x))
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return ret.astype(np.float32)
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