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tirkarthitirkarthi
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Refactor deprecated unittest aliases for Python 3.11 compatibility. (#1324)
1 parent 59aac8a commit fa8187f

29 files changed

+332
-332
lines changed

‎coremltools/test/neural_network/test_custom_neural_nets.py‎

Lines changed: 1 addition & 1 deletion
Original file line numberDiff line numberDiff line change
@@ -82,7 +82,7 @@ def test_fixed_seq_len(self):
8282
coreml_input = {"data": X}
8383
if _is_macos() and _macos_version() >= (10, 13):
8484
coreml_preds = coreml_model.predict(coreml_input)["output"]
85-
self.assertEquals(len(coreml_preds.flatten()), 2)
85+
self.assertEqual(len(coreml_preds.flatten()), 2)
8686

8787
if os.path.exists(model_dir):
8888
shutil.rmtree(model_dir)

‎coremltools/test/neural_network/test_keras.py‎

Lines changed: 105 additions & 105 deletions
Large diffs are not rendered by default.

‎coremltools/test/neural_network/test_keras2.py‎

Lines changed: 109 additions & 109 deletions
Large diffs are not rendered by default.

‎coremltools/test/neural_network/test_keras2_numeric.py‎

Lines changed: 2 additions & 2 deletions
Original file line numberDiff line numberDiff line change
@@ -2903,15 +2903,15 @@ def _run_test(
29032903

29042904
if use_tmp_folder:
29052905
shutil.rmtree(model_dir)
2906-
self.assertEquals(
2906+
self.assertEqual(
29072907
len(coreml_preds),
29082908
len(keras_preds),
29092909
msg="Failed test case %s. Lengths wrong (%s vs %s)"
29102910
% (param, len(coreml_preds), len(keras_preds)),
29112911
)
29122912
for i in range(len(keras_preds)):
29132913
max_den = max(1.0, keras_preds[i], coreml_preds[i])
2914-
self.assertAlmostEquals(
2914+
self.assertAlmostEqual(
29152915
keras_preds[i] / max_den,
29162916
coreml_preds[i] / max_den,
29172917
delta=delta,

‎coremltools/test/neural_network/test_keras_numeric.py‎

Lines changed: 4 additions & 4 deletions
Original file line numberDiff line numberDiff line change
@@ -219,10 +219,10 @@ def _test_keras_model(
219219
kp = k_pred.flatten()
220220
cp = c_preds[idx].flatten()
221221
# Compare predictions
222-
self.assertEquals(len(kp), len(cp))
222+
self.assertEqual(len(kp), len(cp))
223223
for i in range(len(kp)):
224224
max_den = max(1.0, kp[i], cp[i])
225-
self.assertAlmostEquals(
225+
self.assertAlmostEqual(
226226
kp[i] / max_den, cp[i] / max_den, delta=delta
227227
)
228228

@@ -2653,15 +2653,15 @@ def _run_test(
26532653

26542654
if use_tmp_folder:
26552655
shutil.rmtree(model_dir)
2656-
self.assertEquals(
2656+
self.assertEqual(
26572657
len(coreml_preds),
26582658
len(keras_preds),
26592659
msg="Failed test case %s. Lengths wrong (%s vs %s)"
26602660
% (param, len(coreml_preds), len(keras_preds)),
26612661
)
26622662
for i in range(len(keras_preds)):
26632663
max_den = max(1.0, keras_preds[i], coreml_preds[i])
2664-
self.assertAlmostEquals(
2664+
self.assertAlmostEqual(
26652665
keras_preds[i] / max_den,
26662666
coreml_preds[i] / max_den,
26672667
delta=delta,

‎coremltools/test/neural_network/test_multiple_images_preprocessing.py‎

Lines changed: 4 additions & 4 deletions
Original file line numberDiff line numberDiff line change
@@ -107,9 +107,9 @@ def test_keras_1_image_bias(self):
107107
coreml_input_dict["data"] = PIL.Image.fromarray(data.astype(np.uint8))
108108
coreml_preds = coreml_model.predict(coreml_input_dict)["output"].flatten()
109109

110-
self.assertEquals(len(keras_preds), len(coreml_preds))
110+
self.assertEqual(len(keras_preds), len(coreml_preds))
111111
max_relative_error = compare_models(keras_preds, coreml_preds)
112-
self.assertAlmostEquals(max(max_relative_error, 0.001), 0.001, delta=1e-6)
112+
self.assertAlmostEqual(max(max_relative_error, 0.001), 0.001, delta=1e-6)
113113

114114
if os.path.exists(model_dir):
115115
shutil.rmtree(model_dir)
@@ -183,9 +183,9 @@ def test_keras_2_image_bias(self):
183183
coreml_preds = coreml_model.predict(coreml_input_dict)["output"].flatten()
184184

185185
# compare
186-
self.assertEquals(len(keras_preds), len(coreml_preds))
186+
self.assertEqual(len(keras_preds), len(coreml_preds))
187187
max_relative_error = compare_models(keras_preds, coreml_preds)
188-
self.assertAlmostEquals(max(max_relative_error, 0.001), 0.001, delta=1e-6)
188+
self.assertAlmostEqual(max(max_relative_error, 0.001), 0.001, delta=1e-6)
189189

190190
if os.path.exists(model_dir):
191191
shutil.rmtree(model_dir)

‎coremltools/test/neural_network/test_neural_networks.py‎

Lines changed: 3 additions & 3 deletions
Original file line numberDiff line numberDiff line change
@@ -73,7 +73,7 @@ def test_classifier(self):
7373
inputs = np.random.rand(input_dim)
7474
outputs = coremlmodel.predict({"input": inputs})
7575
# this checks that the dictionary got the right name and type
76-
self.assertEquals(type(outputs[output_names[0]]), type({"a": 0.5}))
76+
self.assertEqual(type(outputs[output_names[0]]), type({"a": 0.5}))
7777

7878
def test_classifier_no_name(self):
7979
np.random.seed(1988)
@@ -112,7 +112,7 @@ def test_classifier_no_name(self):
112112
inputs = np.random.rand(input_dim)
113113
outputs = coremlmodel.predict({"input": inputs})
114114
# this checks that the dictionary got the right name and type
115-
self.assertEquals(type(outputs[output_names[0]]), type({"a": 0.5}))
115+
self.assertEqual(type(outputs[output_names[0]]), type({"a": 0.5}))
116116

117117
def test_internal_layer(self):
118118

@@ -171,7 +171,7 @@ def test_internal_layer(self):
171171
partialOutput = coreml2.predict({"input": inputs})
172172

173173
for i in range(0, num_channels2):
174-
self.assertAlmostEquals(
174+
self.assertAlmostEqual(
175175
fullOutputs["middle_layer_output"][i],
176176
partialOutput["output2"][i],
177177
2,

‎coremltools/test/neural_network/test_nn_builder.py‎

Lines changed: 6 additions & 6 deletions
Original file line numberDiff line numberDiff line change
@@ -500,10 +500,10 @@ def test_set_input(self):
500500
builder = self._build_nn_with_one_ip_layer()
501501
builder.set_input(input_names=["data_renamed"], input_dims=[(2,)])
502502

503-
self.assertEquals(
503+
self.assertEqual(
504504
builder.spec.description.input[0].type.multiArrayType.shape[0], 2
505505
)
506-
self.assertEquals(builder.spec.description.input[0].name, "data_renamed")
506+
self.assertEqual(builder.spec.description.input[0].name, "data_renamed")
507507

508508
def test_set_input_fail(self):
509509
builder = self._build_nn_with_one_ip_layer()
@@ -516,10 +516,10 @@ def test_set_output(self):
516516
builder = self._build_nn_with_one_ip_layer()
517517
builder.set_output(output_names=["out_renamed"], output_dims=[(2,)])
518518

519-
self.assertEquals(
519+
self.assertEqual(
520520
builder.spec.description.output[0].type.multiArrayType.shape[0], 2
521521
)
522-
self.assertEquals(builder.spec.description.output[0].name, "out_renamed")
522+
self.assertEqual(builder.spec.description.output[0].name, "out_renamed")
523523

524524
def test_set_output_fail(self):
525525
builder = self._build_nn_with_one_ip_layer()
@@ -598,9 +598,9 @@ def _test_use_float_array_helper(self, use_float_arraytype):
598598
else coremltools.proto.FeatureTypes_pb2.ArrayFeatureType.DOUBLE
599599
)
600600
for input in spec.description.input:
601-
self.assertEquals(input.type.multiArrayType.dataType, array_feature_type)
601+
self.assertEqual(input.type.multiArrayType.dataType, array_feature_type)
602602
for output in spec.description.input:
603-
self.assertEquals(output.type.multiArrayType.dataType, array_feature_type)
603+
self.assertEqual(output.type.multiArrayType.dataType, array_feature_type)
604604

605605
# Assert that the generated spec is functional
606606
mlmodel = MLModel(spec)

‎coremltools/test/neural_network/test_numpy_nn_layers.py‎

Lines changed: 2 additions & 2 deletions
Original file line numberDiff line numberDiff line change
@@ -239,7 +239,7 @@ def test_tiny_upsample_linear_mode(self):
239239
}
240240

241241
self._test_model(builder.spec, input, expected)
242-
self.assertEquals(len(input_dim), builder._get_rank("output"))
242+
self.assertEqual(len(input_dim), builder._get_rank("output"))
243243

244244
def test_LRN(self):
245245
input_dim = (1, 3, 3)
@@ -6713,7 +6713,7 @@ def upsample_pytorch_test(self, h, w, scale_h, scale_w, align_corners, cpu_only)
67136713
expected = {"output": pytorch_output.numpy()}
67146714

67156715
self._test_model(builder.spec, input, expected, useCPUOnly=cpu_only)
6716-
self.assertEquals(len(input_dim), builder._get_rank("output"))
6716+
self.assertEqual(len(input_dim), builder._get_rank("output"))
67176717

67186718
def test_slice_by_size_cpu(self, cpu_only=True):
67196719

‎coremltools/test/neural_network/test_recurrent_stress_tests.py‎

Lines changed: 18 additions & 18 deletions
Original file line numberDiff line numberDiff line change
@@ -736,7 +736,7 @@ def _test_rnn_layer(self, keras_major_version, limit=None):
736736
"output"
737737
].flatten()
738738
try:
739-
self.assertEquals(coreml_preds.shape, keras_preds.shape)
739+
self.assertEqual(coreml_preds.shape, keras_preds.shape)
740740
except AssertionError:
741741
print(
742742
"Shape error:\nbase_params: {}\nkeras_preds.shape: {}\ncoreml_preds.shape: {}".format(
@@ -765,10 +765,10 @@ def _test_rnn_layer(self, keras_major_version, limit=None):
765765
numerical_err_models.append(base_params)
766766
i += 1
767767

768-
self.assertEquals(
768+
self.assertEqual(
769769
shape_err_models, [], msg="Shape error models {}".format(shape_err_models)
770770
)
771-
self.assertEquals(
771+
self.assertEqual(
772772
numerical_err_models,
773773
[],
774774
msg="Numerical error models {}\n"
@@ -922,7 +922,7 @@ def _test_bilstm_layer(self, batched=False):
922922
K.tensorflow_backend._SESSION = None
923923

924924
try:
925-
self.assertEquals(coreml_preds.shape, keras_preds.shape)
925+
self.assertEqual(coreml_preds.shape, keras_preds.shape)
926926
except AssertionError:
927927
print(
928928
"Shape error:\n param: {}\n\n keras_preds.shape: {}\n\n coreml_preds.shape: {}".format(
@@ -971,10 +971,10 @@ def _test_bilstm_layer(self, batched=False):
971971

972972
i += 1
973973

974-
self.assertEquals(
974+
self.assertEqual(
975975
shape_err_models, [], msg="Shape error models {}".format(shape_err_models)
976976
)
977-
self.assertEquals(
977+
self.assertEqual(
978978
numerical_err_models,
979979
[],
980980
msg="Numerical error models {}".format(numerical_err_models),
@@ -1057,7 +1057,7 @@ def _test_batched_lstm_layer(self):
10571057
K.tensorflow_backend._SESSION = None
10581058

10591059
try:
1060-
self.assertEquals(coreml_preds.shape, keras_preds.shape)
1060+
self.assertEqual(coreml_preds.shape, keras_preds.shape)
10611061
except AssertionError:
10621062
print(
10631063
"Shape error:\n param: {}\n\n keras_preds.shape: {}\n\n coreml_preds.shape: {}".format(
@@ -1107,10 +1107,10 @@ def _test_batched_lstm_layer(self):
11071107

11081108
i += 1
11091109

1110-
self.assertEquals(
1110+
self.assertEqual(
11111111
shape_err_models, [], msg="Shape error models {}".format(shape_err_models)
11121112
)
1113-
self.assertEquals(
1113+
self.assertEqual(
11141114
numerical_err_models,
11151115
[],
11161116
msg="Numerical error models {}".format(numerical_err_models),
@@ -1242,7 +1242,7 @@ def _test_lstm_layer(self, keras_major_version, limit=None):
12421242
K.tensorflow_backend._SESSION = None
12431243

12441244
try:
1245-
self.assertEquals(coreml_preds.shape, keras_preds.shape)
1245+
self.assertEqual(coreml_preds.shape, keras_preds.shape)
12461246
except AssertionError:
12471247
print(
12481248
"Shape error:\n base_params: {}\n\n lstm_params: {}\n\n keras_preds.shape: {}\n\n coreml_preds.shape: {}".format(
@@ -1278,10 +1278,10 @@ def _test_lstm_layer(self, keras_major_version, limit=None):
12781278
numerical_failiure += 1
12791279
numerical_err_models.append(base_params)
12801280

1281-
self.assertEquals(
1281+
self.assertEqual(
12821282
shape_err_models, [], msg="Shape error models {}".format(shape_err_models)
12831283
)
1284-
self.assertEquals(
1284+
self.assertEqual(
12851285
numerical_err_models,
12861286
[],
12871287
msg="Numerical error models {}".format(numerical_err_models),
@@ -1416,7 +1416,7 @@ def _test_gru_layer(self, keras_major_version, limit=None):
14161416
K.tensorflow_backend._SESSION.close()
14171417
K.tensorflow_backend._SESSION = None
14181418
try:
1419-
self.assertEquals(coreml_preds.shape, keras_preds.shape)
1419+
self.assertEqual(coreml_preds.shape, keras_preds.shape)
14201420
except AssertionError:
14211421
print(
14221422
"Shape error:\nbase_params: {}\n gru_params: {}\nkeras_preds.shape: {}\ncoreml_preds.shape: {}".format(
@@ -1454,10 +1454,10 @@ def _test_gru_layer(self, keras_major_version, limit=None):
14541454
numerical_err_models.append(base_params)
14551455
i += 1
14561456

1457-
self.assertEquals(
1457+
self.assertEqual(
14581458
shape_err_models, [], msg="Shape error models {}".format(shape_err_models)
14591459
)
1460-
self.assertEquals(
1460+
self.assertEqual(
14611461
numerical_err_models,
14621462
[],
14631463
msg="Numerical error models {}".format(numerical_err_models),
@@ -1607,7 +1607,7 @@ def _test_lstm_stacked(self, keras_major_version, limit=None):
16071607
K.tensorflow_backend._SESSION.close()
16081608
K.tensorflow_backend._SESSION = None
16091609
try:
1610-
self.assertEquals(coreml_preds.shape, keras_preds.shape)
1610+
self.assertEqual(coreml_preds.shape, keras_preds.shape)
16111611
except AssertionError:
16121612
print(
16131613
"Shape error:\nbase_params: {}\nkeras_preds.shape: {}\ncoreml_preds.shape: {}".format(
@@ -1635,10 +1635,10 @@ def _test_lstm_stacked(self, keras_major_version, limit=None):
16351635
numerical_failiure += 1
16361636
numerical_err_models.append(base_params)
16371637
i += 1
1638-
self.assertEquals(
1638+
self.assertEqual(
16391639
shape_err_models, [], msg="Shape error models {}".format(shape_err_models)
16401640
)
1641-
self.assertEquals(
1641+
self.assertEqual(
16421642
numerical_err_models,
16431643
[],
16441644
msg="Numerical error models {}".format(numerical_err_models),

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