fixed method name in unit tests

Author: meownoid

tests/unit/test_common.py

@@ -16,7 +16,7 @@
 import itertools
 from scipy.sparse import coo_matrix
 from sagemaker.amazon.common import (record_deserializer, write_numpy_to_dense_tensor, _read_recordio,
-                                     numpy_to_record_serializer, write_numpy_to_sparse_tensor)
+                                     numpy_to_record_serializer, write_spmatrix_to_sparse_tensor)
 from sagemaker.amazon.record_pb2 import Record
 
 
@@ -135,12 +135,12 @@ def test_invalid_label():
             write_numpy_to_dense_tensor(f, array, label_data)
 
 
-def test_dense_float_write_numpy_to_sparse_tensor():
+def test_dense_float_write_spmatrix_to_sparse_tensor():
     array_data = [[1.0, 2.0, 3.0], [10.0, 20.0, 30.0]]
     keys_data = [[0, 1, 2], [0, 1, 2]]
     array = coo_matrix(np.array(array_data))
     with tempfile.TemporaryFile() as f:
-        write_numpy_to_sparse_tensor(f, array)
+        write_spmatrix_to_sparse_tensor(f, array)
         f.seek(0)
         for record_data, expected_data, expected_keys in zip(_read_recordio(f), array_data, keys_data):
             record = Record()
@@ -150,12 +150,12 @@ def test_dense_float_write_numpy_to_sparse_tensor():
             assert record.features["values"].float64_tensor.shape == [len(expected_data)]
 
 
-def test_dense_float32_write_numpy_to_sparse_tensor():
+def test_dense_float32_write_spmatrix_to_sparse_tensor():
     array_data = [[1.0, 2.0, 3.0], [10.0, 20.0, 30.0]]
     keys_data = [[0, 1, 2], [0, 1, 2]]
     array = coo_matrix(np.array(array_data).astype(np.dtype('float32')))
     with tempfile.TemporaryFile() as f:
-        write_numpy_to_sparse_tensor(f, array)
+        write_spmatrix_to_sparse_tensor(f, array)
         f.seek(0)
         for record_data, expected_data, expected_keys in zip(_read_recordio(f), array_data, keys_data):
             record = Record()
@@ -165,12 +165,12 @@ def test_dense_float32_write_numpy_to_sparse_tensor():
             assert record.features["values"].float32_tensor.shape == [len(expected_data)]
 
 
-def test_dense_int_write_numpy_to_sparse_tensor():
+def test_dense_int_write_spmatrix_to_sparse_tensor():
     array_data = [[1.0, 2.0, 3.0], [10.0, 20.0, 30.0]]
     keys_data = [[0, 1, 2], [0, 1, 2]]
     array = coo_matrix(np.array(array_data).astype(np.dtype('int')))
     with tempfile.TemporaryFile() as f:
-        write_numpy_to_sparse_tensor(f, array)
+        write_spmatrix_to_sparse_tensor(f, array)
         f.seek(0)
         for record_data, expected_data, expected_keys in zip(_read_recordio(f), array_data, keys_data):
             record = Record()
@@ -180,13 +180,13 @@ def test_dense_int_write_numpy_to_sparse_tensor():
             assert record.features["values"].int32_tensor.shape == [len(expected_data)]
 
 
-def test_dense_int_numpy_to_sparse_label():
+def test_dense_int_spmatrix_to_sparse_label():
     array_data = [[1, 2, 3], [10, 20, 3]]
     keys_data = [[0, 1, 2], [0, 1, 2]]
     array = coo_matrix(np.array(array_data))
     label_data = np.array([99, 98, 97])
     with tempfile.TemporaryFile() as f:
-        write_numpy_to_sparse_tensor(f, array, label_data)
+        write_spmatrix_to_sparse_tensor(f, array, label_data)
         f.seek(0)
         for record_data, expected_data, expected_keys, label in zip(
                 _read_recordio(f),
@@ -202,13 +202,13 @@ def test_dense_int_numpy_to_sparse_label():
             assert record.features["values"].int32_tensor.shape == [len(expected_data)]
 
 
-def test_dense_float32_numpy_to_sparse_label():
+def test_dense_float32_spmatrix_to_sparse_label():
     array_data = [[1, 2, 3], [10, 20, 3]]
     keys_data = [[0, 1, 2], [0, 1, 2]]
     array = coo_matrix(np.array(array_data).astype('float32'))
     label_data = np.array([99, 98, 97])
     with tempfile.TemporaryFile() as f:
-        write_numpy_to_sparse_tensor(f, array, label_data)
+        write_spmatrix_to_sparse_tensor(f, array, label_data)
         f.seek(0)
         for record_data, expected_data, expected_keys, label in zip(
                 _read_recordio(f),
@@ -224,13 +224,13 @@ def test_dense_float32_numpy_to_sparse_label():
             assert record.features["values"].float32_tensor.shape == [len(expected_data)]
 
 
-def test_dense_float64_numpy_to_sparse_label():
+def test_dense_float64_spmatrix_to_sparse_label():
     array_data = [[1, 2, 3], [10, 20, 3]]
     keys_data = [[0, 1, 2], [0, 1, 2]]
     array = coo_matrix(np.array(array_data).astype('float64'))
     label_data = np.array([99, 98, 97])
     with tempfile.TemporaryFile() as f:
-        write_numpy_to_sparse_tensor(f, array, label_data)
+        write_spmatrix_to_sparse_tensor(f, array, label_data)
         f.seek(0)
         for record_data, expected_data, expected_keys, label in zip(
                 _read_recordio(f),
@@ -252,10 +252,10 @@ def test_invalid_sparse_label():
     label_data = np.array([99, 98, 97, 1000]).astype(np.dtype('float64'))
     with tempfile.TemporaryFile() as f:
         with pytest.raises(ValueError):
-            write_numpy_to_sparse_tensor(f, array, label_data)
+            write_spmatrix_to_sparse_tensor(f, array, label_data)
 
 
-def test_sparse_float_write_numpy_to_sparse_tensor():
+def test_sparse_float_write_spmatrix_to_sparse_tensor():
     n = 4
     array_data = [[1.0, 2.0], [10.0, 30.0], [100.0, 200.0, 300.0, 400.0], [1000.0, 2000.0, 3000.0]]
     keys_data = [[0, 1], [1, 2], [0, 1, 2, 3], [0, 2, 3]]
@@ -267,7 +267,7 @@ def test_sparse_float_write_numpy_to_sparse_tensor():
 
     array = coo_matrix((flatten_data, (x_indices, y_indices)), dtype='float64')
     with tempfile.TemporaryFile() as f:
-        write_numpy_to_sparse_tensor(f, array)
+        write_spmatrix_to_sparse_tensor(f, array)
         f.seek(0)
         for record_data, expected_data, expected_keys in zip(_read_recordio(f), array_data, keys_data):
             record = Record()
@@ -277,7 +277,7 @@ def test_sparse_float_write_numpy_to_sparse_tensor():
             assert record.features["values"].float64_tensor.shape == [n]
 
 
-def test_sparse_float32_write_numpy_to_sparse_tensor():
+def test_sparse_float32_write_spmatrix_to_sparse_tensor():
     n = 4
     array_data = [[1.0, 2.0], [10.0, 30.0], [100.0, 200.0, 300.0, 400.0], [1000.0, 2000.0, 3000.0]]
     keys_data = [[0, 1], [1, 2], [0, 1, 2, 3], [0, 2, 3]]
@@ -289,7 +289,7 @@ def test_sparse_float32_write_numpy_to_sparse_tensor():
 
     array = coo_matrix((flatten_data, (x_indices, y_indices)), dtype='float32')
     with tempfile.TemporaryFile() as f:
-        write_numpy_to_sparse_tensor(f, array)
+        write_spmatrix_to_sparse_tensor(f, array)
         f.seek(0)
         for record_data, expected_data, expected_keys in zip(_read_recordio(f), array_data, keys_data):
             record = Record()
@@ -299,7 +299,7 @@ def test_sparse_float32_write_numpy_to_sparse_tensor():
             assert record.features["values"].float32_tensor.shape == [n]
 
 
-def test_sparse_int_write_numpy_to_sparse_tensor():
+def test_sparse_int_write_spmatrix_to_sparse_tensor():
     n = 4
     array_data = [[1.0, 2.0], [10.0, 30.0], [100.0, 200.0, 300.0, 400.0], [1000.0, 2000.0, 3000.0]]
     keys_data = [[0, 1], [1, 2], [0, 1, 2, 3], [0, 2, 3]]
@@ -311,7 +311,7 @@ def test_sparse_int_write_numpy_to_sparse_tensor():
 
     array = coo_matrix((flatten_data, (x_indices, y_indices)), dtype='int')
     with tempfile.TemporaryFile() as f:
-        write_numpy_to_sparse_tensor(f, array)
+        write_spmatrix_to_sparse_tensor(f, array)
         f.seek(0)
         for record_data, expected_data, expected_keys in zip(_read_recordio(f), array_data, keys_data):
             record = Record()
@@ -321,10 +321,10 @@ def test_sparse_int_write_numpy_to_sparse_tensor():
             assert record.features["values"].int32_tensor.shape == [n]
 
 
-def test_dense_to_sparse_array():
+def test_dense_to_sparse():
     array_data = [[1, 2, 3], [10, 20, 3]]
     array = np.array(array_data)
     label_data = np.array([99, 98, 97]).astype(np.dtype('float64'))
     with tempfile.TemporaryFile() as f:
         with pytest.raises(TypeError):
-            write_numpy_to_sparse_tensor(f, array, label_data)
+            write_spmatrix_to_sparse_tensor(f, array, label_data)