[QNN][TFLite] Parsing TFLite quantized models. (#3900)

tests/python/frontend/tflite/test_forward.py

@@ -997,6 +997,46 @@ def test_forward_inception_v4_net():
     tvm.testing.assert_allclose(np.squeeze(tvm_output[0]), np.squeeze(tflite_output[0]),
                                 rtol=1e-5, atol=1e-5)
 
+def test_forward_qnn_inception_v1_net():
+    """Test the Quantized TFLite Inception model."""
+    # InceptionV1
+    tflite_model_file = tf_testing.get_workload_official(
+        "https://storage.googleapis.com/download.tensorflow.org/models/inception_v1_224_quant_20181026.tgz",
+        "inception_v1_224_quant.tflite")
+    with open(tflite_model_file, "rb") as f:
+        tflite_model_buf = f.read()
+    # Checking the labels because the requantize implementation is different between TFLite and
+    # Relay. This cause final output numbers to mismatch. So, testing accuracy via labels.
+    np.random.seed(0)
+    data = np.random.random_integers(low=0, high=128, size=(1, 224, 224, 3)).astype('uint8')
+    tflite_output = run_tflite_graph(tflite_model_buf, data)
+    tflite_predictions = np.squeeze(tflite_output)
+    tflite_sorted_labels = tflite_predictions.argsort()[-3:][::-1]
+    tvm_output = run_tvm_graph(tflite_model_buf, data, 'input')
+    tvm_predictions = np.squeeze(tvm_output)
+    tvm_sorted_labels = tvm_predictions.argsort()[-3:][::-1]
+    tvm.testing.assert_allclose(tvm_sorted_labels, tflite_sorted_labels)
+
+def test_forward_qnn_mobilenet_v1_net():
+    """Test the Quantized TFLite Mobilenet V1 model."""
+    # MobilenetV1
+    tflite_model_file = tf_testing.get_workload_official(
+        "https://storage.googleapis.com/download.tensorflow.org/models/mobilenet_v1_2018_08_02/mobilenet_v1_1.0_224_quant.tgz",
+        "mobilenet_v1_1.0_224_quant.tflite")
+    with open(tflite_model_file, "rb") as f:
+        tflite_model_buf = f.read()
+    # Checking the labels because the requantize implementation is different between TFLite and
+    # Relay. This cause final output numbers to mismatch. So, testing accuracy via labels.
+    np.random.seed(0)
+    data = np.random.random_integers(low=0, high=128, size=(1, 224, 224, 3)).astype('uint8')
+    tflite_output = run_tflite_graph(tflite_model_buf, data)
+    tflite_predictions = np.squeeze(tflite_output)
+    tflite_sorted_labels = tflite_predictions.argsort()[-3:][::-1]
+    tvm_output = run_tvm_graph(tflite_model_buf, data, 'input')
+    tvm_predictions = np.squeeze(tvm_output)
+    tvm_sorted_labels = tvm_predictions.argsort()[-3:][::-1]
+    tvm.testing.assert_allclose(tvm_sorted_labels, tflite_sorted_labels)
+
 #######################################################################
 # SSD Mobilenet
 # -------------
@@ -1069,3 +1109,8 @@ if __name__ == '__main__':
     test_forward_inception_v3_net()
     test_forward_inception_v4_net()
     test_forward_ssd_mobilenet_v1()
+
+    # End to End quantized
+    # TODO - MobilenetV2 fails for now. Remove when fixed.
+    test_forward_qnn_inception_v1_net()
+    test_forward_qnn_mobilenet_v1_net()