ekalda commented on a change in pull request #9457:
URL: https://github.com/apache/tvm/pull/9457#discussion_r750119977
##########
File path: tests/python/contrib/test_ethosu/test_codegen.py
##########
@@ -343,5 +343,178 @@ def representative_dataset():
infra.verify_source(compiled_models, accel_type)
[email protected]("accel_type", ACCEL_TYPES)
[email protected]("ifm_shape", [(3, 2), (1, 15, 11, 7), (3, 1, 12),
(400,)])
[email protected]("ifm_scale, ifm_zp, ofm_scale, ofm_zp", [(1, 0, 1,
0), (0.015, 3, 0.2, 5)])
+def test_ethosu_identity_codegen(ifm_shape, ifm_scale, ifm_zp, ofm_scale,
ofm_zp, accel_type):
+ # Create a "partitioned" Relay function
+ ifm = relay.var("ifm", shape=ifm_shape, dtype="int8")
+ ifm0 = relay.var("ifm0", shape=ifm_shape, dtype="int8")
+ identity = infra.make_ethosu_identity(
+ ifm0, ifm_scale=ifm_scale, ifm_zero_point=ifm_zp, ofm_scale=ofm_scale,
ofm_zero_point=ofm_zp
+ )
+ glb_ethosu = relay.GlobalVar("tvmgen_default_ethosu_main_0")
+
+ func = (
+ relay.Function([ifm0], identity)
+ .with_attr("Inline", 1)
+ .with_attr("Compiler", "ethosu")
+ .with_attr("global_symbol", "tvmgen_default_ethosu_main_0")
+ .with_attr("Primitive", 1)
+ )
+ mod = tvm.IRModule()
+ mod[glb_ethosu] = func
+ mod = relay.transform.InferType()(mod)
+
+ call = relay.Call(glb_ethosu, [ifm])
+ mod["main"] = relay.Function([ifm], call)
+ mod = relay.transform.InferType()(mod)
+
+ in_data = np.random.randint(-120, high=120, size=ifm_shape, dtype="int8")
+ requant_data = (ifm_scale * (in_data - ifm_zp)) / ofm_scale + ofm_zp
+ out_data = np.round(np.clip(requant_data, -128, 127)).astype("int8")
+
+ compiled_model = infra.build_source(
+ mod, {"ifm": in_data}, [out_data], accel_type, output_tolerance=1
+ )
+
+ imported_modules = compiled_model[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")
+ cmms = get_cs(ethosu_module)
+ cmms = bytes.fromhex(cmms)
+
+ infra.print_payload(cmms)
+ infra.verify_source(compiled_model, accel_type)
+
+
[email protected]("accel_type", ACCEL_TYPES)
[email protected](
Review comment:
Done
##########
File path: tests/python/contrib/test_ethosu/test_codegen.py
##########
@@ -343,5 +343,178 @@ def representative_dataset():
infra.verify_source(compiled_models, accel_type)
[email protected]("accel_type", ACCEL_TYPES)
[email protected]("ifm_shape", [(3, 2), (1, 15, 11, 7), (3, 1, 12),
(400,)])
[email protected]("ifm_scale, ifm_zp, ofm_scale, ofm_zp", [(1, 0, 1,
0), (0.015, 3, 0.2, 5)])
+def test_ethosu_identity_codegen(ifm_shape, ifm_scale, ifm_zp, ofm_scale,
ofm_zp, accel_type):
+ # Create a "partitioned" Relay function
+ ifm = relay.var("ifm", shape=ifm_shape, dtype="int8")
+ ifm0 = relay.var("ifm0", shape=ifm_shape, dtype="int8")
+ identity = infra.make_ethosu_identity(
+ ifm0, ifm_scale=ifm_scale, ifm_zero_point=ifm_zp, ofm_scale=ofm_scale,
ofm_zero_point=ofm_zp
+ )
+ glb_ethosu = relay.GlobalVar("tvmgen_default_ethosu_main_0")
+
+ func = (
+ relay.Function([ifm0], identity)
+ .with_attr("Inline", 1)
+ .with_attr("Compiler", "ethosu")
+ .with_attr("global_symbol", "tvmgen_default_ethosu_main_0")
+ .with_attr("Primitive", 1)
+ )
+ mod = tvm.IRModule()
+ mod[glb_ethosu] = func
+ mod = relay.transform.InferType()(mod)
+
+ call = relay.Call(glb_ethosu, [ifm])
+ mod["main"] = relay.Function([ifm], call)
+ mod = relay.transform.InferType()(mod)
+
+ in_data = np.random.randint(-120, high=120, size=ifm_shape, dtype="int8")
+ requant_data = (ifm_scale * (in_data - ifm_zp)) / ofm_scale + ofm_zp
+ out_data = np.round(np.clip(requant_data, -128, 127)).astype("int8")
+
+ compiled_model = infra.build_source(
+ mod, {"ifm": in_data}, [out_data], accel_type, output_tolerance=1
+ )
+
+ imported_modules = compiled_model[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")
+ cmms = get_cs(ethosu_module)
+ cmms = bytes.fromhex(cmms)
+
+ infra.print_payload(cmms)
+ infra.verify_source(compiled_model, accel_type)
+
+
[email protected]("accel_type", ACCEL_TYPES)
[email protected](
+ "ifm_shape, new_shape",
+ [
+ ((1, 4, 1, 2), (1, 1, 1, 8)),
+ (
+ (
+ 5,
+ 1,
+ 20,
+ ),
+ (1, 5, 1, 20),
+ ),
+ ((12, 20), (1, 6, 4, 10)),
+ ((12, 20), (6, 4, 10)),
+ ((20,), (4, 5)),
+ ],
+)
+def test_relay_reshape_codegen(ifm_shape, new_shape, accel_type):
+ # Create a "partitioned" Relay graph
Review comment:
Done
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