Twitter Recommendation Algorithm

Please note we have force-pushed a new initial commit in order to remove some publicly-available Twitter user information. Note that this process may be required in the future.

twml/twml_common/sparse_inputs.py

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+import numpy as np
+import tensorflow.compat.v1 as tf
+
+
+def create_sparse_tensor(batch_size, input_size, num_values, dtype=tf.float32):
+  random_indices = np.sort(np.random.randint(batch_size * input_size, size=num_values))
+  test_indices_i = random_indices // input_size
+  test_indices_j = random_indices % input_size
+  test_indices = np.stack([test_indices_i, test_indices_j], axis=1)
+  test_values = np.random.random(num_values).astype(dtype.as_numpy_dtype)
+
+  return tf.SparseTensor(indices=tf.constant(test_indices),
+                         values=tf.constant(test_values),
+                         dense_shape=(batch_size, input_size))
+
+
+def create_reference_input(sparse_input, use_binary_values):
+  if use_binary_values:
+    sp_a = tf.SparseTensor(indices=sparse_input.indices,
+                           values=tf.ones_like(sparse_input.values),
+                           dense_shape=sparse_input.dense_shape)
+  else:
+    sp_a = sparse_input
+  return sp_a