dchauhan-arm commented on a change in pull request #10345:
URL: https://github.com/apache/tvm/pull/10345#discussion_r813708528
##########
File path: tests/python/contrib/test_ethosu/test_codegen.py
##########
@@ -1167,5 +1167,24 @@ def leaky_relu_func(x):
_compare_tvm_with_tflite(leaky_relu_func, [ifm_shape], accel_type)
[email protected]("accel_type", ACCEL_TYPES)
[email protected]("units", [32, 64])
[email protected]("use_bias", [True, False])
[email protected]("activation_function", ["RELU", "NONE"])
+def test_tflite_fully_connected(
+ accel_type,
+ units,
+ use_bias,
+ activation_function,
+):
+ @tf.function
+ def fully_connected():
+ return tf.keras.layers.Dense(
Review comment:
this is a very welcome change, I'l try and make this work!
##########
File path: python/tvm/relay/op/contrib/ethosu.py
##########
@@ -1537,6 +1537,105 @@ def squeeze_pattern():
return is_op("squeeze")(wildcard())
+class FullyConnectedParams:
+ """
+ This class will parse a call to an ethos-u.fully_connected composite
+ function and extract the parameter information.
+ """
+
+ composite_name = "ethosu.fully_connected"
+ activation_map = {"clip": "CLIP"}
+
+ @requires_vela
+ def __init__(self, func_body):
+ from tvm.relay.backend.contrib.ethosu.util import QDenseArgs # type:
ignore
+ from tvm.relay.backend.contrib.ethosu.util import BiasAddArgs
+ from tvm.relay.backend.contrib.ethosu.util import RequantArgs
+
+ activation = None
+ if str(func_body.op) in self.activation_map.keys():
+ activation = func_body
+ requantize_op = activation.args[0]
+ else:
+ requantize_op = func_body
+
+ bias_add = requantize_op.args[0]
+ qnn_dense = bias_add.args[0]
+
+ # We consider the weights & biases as params as they should be constant
+ self.weights = TensorParams(
+ qnn_dense.args[QDenseArgs.weights.value],
+ "OI",
+ qnn_dense.args[QDenseArgs.weights_scale.value],
+ qnn_dense.args[QDenseArgs.weights_zero_point.value],
+ )
+ self.biases = TensorParams(
+ bias_add.args[BiasAddArgs.BIASES.value],
+ None,
+ requantize_op.args[RequantArgs.IFM_SCALE.value],
+ requantize_op.args[RequantArgs.IFM_ZERO_POINT.value],
+ )
+ self.ifm = TensorParams(
+ qnn_dense.args[QDenseArgs.ifm.value],
Review comment:
ack!
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