jacobbohlin commented on a change in pull request #10242:
URL: https://github.com/apache/tvm/pull/10242#discussion_r806653030
##########
File path: tests/python/contrib/test_ethosu/test_networks.py
##########
@@ -65,5 +65,31 @@ def test_forward_mobilenet_v1(accel_type):
infra.verify_source(compiled_models, accel_type)
+def test_forward_mobilenet_v2(accel_type="ethos-u55-256"):
+ """Test the Mobilenet V2 TF Lite model."""
+ np.random.seed(23)
+ tflite_model_file = tf_testing.get_workload_official(
+ "https://storage.googleapis.com/download.tensorflow.org/models/";
+ "tflite_11_05_08/mobilenet_v2_1.0_224_quant.tgz",
+ "mobilenet_v2_1.0_224_quant.tflite",
+ )
+ with open(tflite_model_file, "rb") as f:
+ tflite_model_buf = f.read()
+ input_tensor = "input"
+ input_dtype = "uint8"
+ input_shape = (1, 224, 224, 3)
+ in_min, in_max = util.get_range_for_dtype_str(input_dtype)
+ input_data = np.random.randint(in_min, high=in_max, size=input_shape,
dtype=input_dtype)
+ relay_mod, params = convert_to_relay(tflite_model_buf)
+ input_data = {input_tensor: input_data}
+ output_data = generate_ref_data(relay_mod, input_data)
+
+ mod = partition_for_ethosu(relay_mod, params)
+ compiled_models = infra.build_source(
+ mod, input_data, output_data, accel_type, output_tolerance=10
+ )
+ infra.verify_source(compiled_models, accel_type)
+
+
if __name__ == "__main__":
- test_forward_mobilenet_v1()
+ test_forward_mobilenet_v1(ACCEL_TYPES[0])
Review comment:
Agreed, that's probably better.
##########
File path: tests/python/contrib/test_ethosu/test_networks.py
##########
@@ -65,5 +65,31 @@ def test_forward_mobilenet_v1(accel_type):
infra.verify_source(compiled_models, accel_type)
+def test_forward_mobilenet_v2(accel_type="ethos-u55-256"):
+ """Test the Mobilenet V2 TF Lite model."""
+ np.random.seed(23)
+ tflite_model_file = tf_testing.get_workload_official(
+ "https://storage.googleapis.com/download.tensorflow.org/models/";
+ "tflite_11_05_08/mobilenet_v2_1.0_224_quant.tgz",
+ "mobilenet_v2_1.0_224_quant.tflite",
+ )
+ with open(tflite_model_file, "rb") as f:
+ tflite_model_buf = f.read()
+ input_tensor = "input"
+ input_dtype = "uint8"
+ input_shape = (1, 224, 224, 3)
+ in_min, in_max = util.get_range_for_dtype_str(input_dtype)
+ input_data = np.random.randint(in_min, high=in_max, size=input_shape,
dtype=input_dtype)
+ relay_mod, params = convert_to_relay(tflite_model_buf)
+ input_data = {input_tensor: input_data}
+ output_data = generate_ref_data(relay_mod, input_data)
+
+ mod = partition_for_ethosu(relay_mod, params)
+ compiled_models = infra.build_source(
+ mod, input_data, output_data, accel_type, output_tolerance=10
Review comment:
I can give that a try.
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