[GitHub] [incubator-tvm] d-smirnov commented on a change in pull request #5848: [TFLite] QNN support for TFLite 2.1.0 quantized models

[GitBox <gi...@apache.org>]

d-smirnov commented on a change in pull request #5848:
URL: https://github.com/apache/incubator-tvm/pull/5848#discussion_r448572493



##########
File path: python/tvm/relay/frontend/tflite.py
##########
@@ -263,21 +305,29 @@ def get_tensor_value(self, tensor_wrapper):
         except ImportError:
             raise ImportError("The tflite package must be installed")
 
+        # Read the data from the buffer. Also extract the shape.
+        # The shape is used later to reshape the data.
+        data = tensor_wrapper.buffer.DataAsNumpy()
+        shape = tensor_wrapper.tensor.ShapeAsNumpy()
+
+        # When TFLite buffer is of size 1 (scalar), then TFLite tensor shape is set to 0.
+        # Therefore, we set the shape to 1 for numpy reshape to work.  Set shape to 1 if the data is
+        # a scalar type
+        if data.size == 1 and isinstance(shape, int) and shape == 0:
+            shape = (1,)
+
+        if tensor_wrapper.tensor.Type() == TensorType.INT8:

Review comment:
       Please consider following change as well:
   ```
       def has_same_qnn_params(self, lhs_tensor, rhs_tensor):
           lhs_scale = lhs_tensor.qnn_params['scale']
           rhs_scale = rhs_tensor.qnn_params['scale']
           lhs_zero_point = lhs_tensor.qnn_params['zero_point']
           rhs_zero_point = rhs_tensor.qnn_params['zero_point']
           return np.allclose( lhs_scale.data.asnumpy(), rhs_scale.data.asnumpy(), rtol=1e-5, atol=1e-5 ) and \
                  np.allclose( lhs_zero_point.data.asnumpy(), rhs_zero_point.data.asnumpy(), rtol=1e-5, atol=1e-5 )
   
   
   ```




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