ekalda commented on a change in pull request #9515:
URL: https://github.com/apache/tvm/pull/9515#discussion_r750487693
##########
File path: tests/python/contrib/test_ethosu/test_codegen.py
##########
@@ -435,6 +435,56 @@ def representative_dataset():
infra.verify_source(compiled_models, accel_type)
[email protected]("accel_type", ACCEL_TYPES)
+def test_binary_add_from_constant_scalar(accel_type):
+ dtype = "uint8"
+ ifm_shape = (1, 4, 4, 8)
+
+ def create_relay_graph():
+ inp = relay.var("input", shape=ifm_shape, dtype=dtype)
+ scalar = relay.const(np.ones((1, 1, 1, 1), dtype=dtype), dtype=dtype)
+ add = relay.qnn.op.add(
+ inp,
+ scalar,
+ relay.const(1.0, dtype="float32"),
+ relay.const(0, dtype="int32"),
+ relay.const(1.0, dtype="float32"),
+ relay.const(0, dtype="int32"),
+ relay.const(1.0, dtype="float32"),
+ relay.const(0, dtype="int32"),
+ )
+ func = relay.Function(relay.analysis.free_vars(add), add)
Review comment:
Is there a reason we start from Relay there instead of TFLite?
##########
File path: tests/python/contrib/test_ethosu/test_encode_constants.py
##########
@@ -270,5 +273,47 @@ def _get_func():
assert reference_const_sizes == test_const_sizes
+def test_constant_as_input():
+ """Test to check that constants specified as inputs aren't
+ interpreted as an encoded constant."""
+
+ def get_graph():
+ dtype = "uint8"
Review comment:
Why does the constant need to be`uint8`? (just asking for enlightenment)
##########
File path: tests/python/contrib/test_ethosu/test_codegen.py
##########
@@ -435,6 +435,56 @@ def representative_dataset():
infra.verify_source(compiled_models, accel_type)
[email protected]("accel_type", ACCEL_TYPES)
+def test_binary_add_from_constant_scalar(accel_type):
+ dtype = "uint8"
+ ifm_shape = (1, 4, 4, 8)
+
+ def create_relay_graph():
+ inp = relay.var("input", shape=ifm_shape, dtype=dtype)
+ scalar = relay.const(np.ones((1, 1, 1, 1), dtype=dtype), dtype=dtype)
+ add = relay.qnn.op.add(
+ inp,
+ scalar,
+ relay.const(1.0, dtype="float32"),
+ relay.const(0, dtype="int32"),
+ relay.const(1.0, dtype="float32"),
+ relay.const(0, dtype="int32"),
+ relay.const(1.0, dtype="float32"),
+ relay.const(0, dtype="int32"),
+ )
+ func = relay.Function(relay.analysis.free_vars(add), add)
+ return tvm.IRModule.from_expr(func)
+
+ mod = create_relay_graph()
+ partitioned_mod = partition_for_ethosu(mod)
+
+ # Generate reference data
+ input_data = {"input": np.random.randint(low=0, high=255, size=ifm_shape,
dtype=dtype)}
+ output_data = generate_ref_data(mod, input_data)
+
+ compiled_models = infra.build_source(
+ partitioned_mod,
+ input_data,
+ output_data,
+ accel_type,
+ output_tolerance=0,
+ )
+
+ # Assumes only two runtime.Modules are created -- i.e. single offload
module
+ imported_modules = compiled_models[0].executor_factory.lib.imported_modules
+ assert len(imported_modules) == 2
+ ethosu_module = imported_modules[0]
+
+ # Verify generated C source
+ get_cs = tvm._ffi.get_global_func("runtime.module.ethosu.getcs")
Review comment:
```suggestion
get_cs = tvm._ffi.get_global_func("runtime.module.ethos-u.getcs")
```
Looks like 'ethos-u' is all the rage now :)
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