Fix initialization of ndarray

Author: insuhan

experimental/__init__.py

@@ -6,16 +6,21 @@
 import neural_tangents
 from neural_tangents import stax
 
-from pkg_resources import parse_version
-if parse_version(neural_tangents.__version__) >= parse_version('0.5.0'):
-  from neural_tangents._src.utils import utils, dataclasses
-  from neural_tangents._src.stax.linear import _pool_kernel, Padding
-  from neural_tangents._src.stax.linear import _Pooling as Pooling
-else:
-  from neural_tangents.utils import utils, dataclasses
-  from neural_tangents.stax import _pool_kernel, Padding, Pooling
-
-from sketching import TensorSRHT2, PolyTensorSRHT
+# from pkg_resources import parse_version
+# if parse_version(neural_tangents.__version__) >= parse_version('0.5.0'):
+#   from neural_tangents._src.utils import utils, dataclasses
+#   from neural_tangents._src.stax.linear import _pool_kernel, Padding
+#   from neural_tangents._src.stax.linear import _Pooling as Pooling
+# else:
+#   from neural_tangents.utils import utils, dataclasses
+#   from neural_tangents.stax import _pool_kernel, Padding, Pooling
+from neural_tangents._src.utils import dataclasses
+# from neural_tangents._src.utils.typing import Optional
+from typing import Optional
+from neural_tangents._src.stax.linear import _pool_kernel, Padding
+from neural_tangents._src.stax.linear import _Pooling as Pooling
+
+from experimental.sketching import TensorSRHT2, PolyTensorSRHT
 """ Implementation for NTK Sketching and Random Features """
 
 
@@ -50,13 +55,13 @@ def kappa1(x):
 
 @dataclasses.dataclass
 class Features:
-  nngp_feat: np.ndarray
-  ntk_feat: np.ndarray
+  nngp_feat: Optional[np.ndarray] = None
+  ntk_feat: Optional[np.ndarray] = None
 
   batch_axis: int = dataclasses.field(pytree_node=False)
   channel_axis: int = dataclasses.field(pytree_node=False)
 
-  replace = ...  # type: Callable[..., 'Features']
+  replace = ... 
 
 
 def _inputs_to_features(x: np.ndarray,
@@ -69,7 +74,7 @@ def _inputs_to_features(x: np.ndarray,
   nngp_feat = x / x.shape[channel_axis]**0.5
   ntk_feat = np.empty((), dtype=nngp_feat.dtype)
 
-  return Features(nngp_feat=nngp_feat,
+  return Features.replace(nngp_feat=nngp_feat,
                   ntk_feat=ntk_feat,
                   batch_axis=batch_axis,
                   channel_axis=channel_axis)

experimental/features.py

@@ -61,8 +61,8 @@ def __init__(self, rng, input_dim, sketch_dim, coeffs):
     degree = len(coeffs) - 1
     self.degree = degree
 
-    self.tree_rand_signs = [0 for i in range((self.degree - 1).bit_length())]
-    self.tree_rand_inds = [0 for i in range((self.degree - 1).bit_length())]
+    self.tree_rand_signs: Optional[np.ndarray] = [0 for i in range((self.degree - 1).bit_length())]
+    self.tree_rand_inds: Optional[np.ndarray] = [0 for i in range((self.degree - 1).bit_length())]
     rng1, rng2, rng3 = random.split(rng, 3)
 
     ske_dim_ = sketch_dim // 4
@@ -92,7 +92,7 @@ def __init__(self, rng, input_dim, sketch_dim, coeffs):
   def sketch(self, x):
     n = x.shape[0]
     log_degree = len(self.tree_rand_signs)
-    V = [0 for i in range(log_degree)]
+    V: Optional[np.ndarray] = [0 for i in range(log_degree)]
     E1 = np.concatenate((np.ones(
         (n, 1), dtype=x.dtype), np.zeros((n, x.shape[-1] - 1), dtype=x.dtype)),
                         1)

experimental/sketching.py

@@ -6,7 +6,7 @@
 config.update("jax_enable_x64", True)
 from neural_tangents import stax
 
-from features import _inputs_to_features, DenseFeatures, ReluFeatures, serial
+from experimental.features import _inputs_to_features, DenseFeatures, ReluFeatures, serial
 
 seed = 1
 n, d = 6, 4

experimental/test_fc_ntk.py

@@ -12,7 +12,7 @@
 from jax import random
 
 from neural_tangents import stax
-from features import ReluFeatures, ConvFeatures, AvgPoolFeatures, serial, FlattenFeatures, DenseFeatures, _inputs_to_features
+from experimental.features import ReluFeatures, ConvFeatures, AvgPoolFeatures, serial, FlattenFeatures, DenseFeatures, _inputs_to_features
 
 layer_factor = {5: [2, 1, 1], 7: [2, 2, 2], 10: [3, 3, 3]}
 width = 1