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Correct runtime.load_module (apache#6161)
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tqchen authored and Trevor Morris committed Aug 26, 2020
1 parent b2b8a80 commit 8a90714
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6 changes: 3 additions & 3 deletions docs/deploy/hls.rst
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Expand Up @@ -64,11 +64,11 @@ We use two python scripts for this tutorial.
tgt="sdaccel"
fadd = tvm.runtime.load("myadd.so")
fadd = tvm.runtime.load_module("myadd.so")
if os.environ.get("XCL_EMULATION_MODE"):
fadd_dev = tvm.runtime.load("myadd.xclbin")
fadd_dev = tvm.runtime.load_module("myadd.xclbin")
else:
fadd_dev = tvm.runtime.load("myadd.awsxclbin")
fadd_dev = tvm.runtime.load_module("myadd.awsxclbin")
fadd.import_module(fadd_dev)
ctx = tvm.context(tgt, 0)
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2 changes: 1 addition & 1 deletion docs/dev/introduction_to_module_serialization.rst
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Expand Up @@ -53,7 +53,7 @@ Let us build one ResNet-18 workload for GPU as an example first.
resnet18_lib.export_library(path_lib)
# load it back
loaded_lib = tvm.runtime.load(path_lib)
loaded_lib = tvm.runtime.load_module(path_lib)
assert loaded_lib.type_key == "library"
assert loaded_lib.imported_modules[0].type_key == "cuda"
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6 changes: 3 additions & 3 deletions docs/dev/relay_bring_your_own_codegen.rst
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Expand Up @@ -905,7 +905,7 @@ We also need to register this function to enable the corresponding Python API:
TVM_REGISTER_GLOBAL("module.loadbinary_examplejson")
.set_body_typed(ExampleJsonModule::LoadFromBinary);

The above registration means when users call ``tvm.runtime.load(lib_path)`` API and the exported library has an ExampleJSON stream, our ``LoadFromBinary`` will be invoked to create the same customized runtime module.
The above registration means when users call ``tvm.runtime.load_module(lib_path)`` API and the exported library has an ExampleJSON stream, our ``LoadFromBinary`` will be invoked to create the same customized runtime module.

In addition, if you want to support module creation directly from an ExampleJSON file, you can also implement a simple function and register a Python API as follows:

Expand All @@ -930,7 +930,7 @@ In addition, if you want to support module creation directly from an ExampleJSON
*rv = ExampleJsonModule::Create(args[0]);
});
It means users can manually write/modify an ExampleJSON file, and use Python API ``tvm.runtime.load("mysubgraph.examplejson", "examplejson")`` to construct a customized module.
It means users can manually write/modify an ExampleJSON file, and use Python API ``tvm.runtime.load_module("mysubgraph.examplejson", "examplejson")`` to construct a customized module.

*******
Summary
Expand All @@ -954,7 +954,7 @@ In summary, here is a checklist for you to refer:
* ``Run`` to execute a subgraph.
* Register a runtime creation API.
* ``SaveToBinary`` and ``LoadFromBinary`` to serialize/deserialize customized runtime module.
* Register ``LoadFromBinary`` API to support ``tvm.runtime.load(your_module_lib_path)``.
* Register ``LoadFromBinary`` API to support ``tvm.runtime.load_module(your_module_lib_path)``.
* (optional) ``Create`` to support customized runtime module construction from subgraph file in your representation.

* An annotator to annotate a user Relay program to make use of your compiler and runtime (TBA).
2 changes: 1 addition & 1 deletion rust/tvm/examples/resnet/src/build_resnet.py
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Expand Up @@ -112,7 +112,7 @@ def download_img_labels():
def test_build(build_dir):
""" Sanity check with random input"""
graph = open(osp.join(build_dir, "deploy_graph.json")).read()
lib = tvm.runtime.load(osp.join(build_dir, "deploy_lib.so"))
lib = tvm.runtime.load_module(osp.join(build_dir, "deploy_lib.so"))
params = bytearray(open(osp.join(build_dir,"deploy_param.params"), "rb").read())
input_data = tvm.nd.array(np.random.uniform(size=data_shape).astype("float32"))
ctx = tvm.cpu()
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