mbaret commented on a change in pull request #6228:
URL: https://github.com/apache/incubator-tvm/pull/6228#discussion_r467972074
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File path: python/tvm/relay/frontend/tflite.py
##########
@@ -1695,10 +1695,9 @@ def convert_fully_connected(self, op):
raise ImportError("The tflite package must be installed")
input_tensors = self.get_input_tensors(op)
- assert len(input_tensors) >= 2, "input tensors length should be >= 2"
+ assert len(input_tensors) in (2, 3), "input tensors length should be
two or three"
Review comment:
input_tensors can now have 3 elements, but I can't see the 3rd tensors
(input_tensors[2]) being used anywhere?
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File path: tests/python/frontend/tflite/test_forward.py
##########
@@ -2456,25 +2456,27 @@ def test_forward_sparse_to_dense():
# Fully Connected
# ---------------
-def _test_fully_connected(tensor_in_sizes, filter_in_sizes, bias_in_size=None):
+def _test_fully_connected(tensor_in_sizes, wrap_input, filter_in_sizes,
bias_in_size=None):
""" One iteration of fully connected """
- total_size_1 = 1
- total_size_2 = 1
- for s in tensor_in_sizes:
- total_size_1 *= s
- for s in filter_in_sizes:
- total_size_2 *= s
- # Initializes the input tensor with array containing incrementing
- # numbers from 1.
- data_array = [f * 1.0 for f in range(1, total_size_1 + 1)]
- filter_array = [f * 1.0 for f in range(1, total_size_2 + 1)]
+ total_size_1 = np.prod( tensor_in_sizes )
+ total_size_2 = np.prod( filter_in_sizes )
+
assert int(total_size_1 / tensor_in_sizes[0]) == filter_in_sizes[0], \
"input size and filter size are mismatched"
+ # Initializes the input tensor with array containing incrementing
+ # numbers from 1.
+ data_array = np.arange(1, total_size_1 + 1, dtype=np.float32)
+ filter_array = np.arange(1, total_size_2 + 1, dtype=np.float32)
+
with tf.Graph().as_default():
- in_data = array_ops.placeholder(shape=tensor_in_sizes, dtype='float32')
- in_filter = constant_op.constant(filter_array, shape=filter_in_sizes,
dtype='float32')
+ in_name="input"
Review comment:
```suggestion
in_name = "input"
```
##########
File path: python/tvm/relay/frontend/tflite.py
##########
@@ -1720,7 +1719,7 @@ def convert_fully_connected(self, op):
# Dense expected Weight shape: [out_dim, n_units]
# Dense output shape: [batch_size, out_dim]
target_shape = tuple((-1, weight_tensor_shape[1]))
- in_expr = self.get_expr(input_tensor_idx)
+ in_expr = self.get_tensor_expr(input_tensor)
Review comment:
Is this a related change?
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