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[CI] Upgrade CI image to 20241105-030952-3e386fd3 (#17451)
* use `20241105-030952-3e386fd3` for ci * fix missing `language` kwarg in save_rst_example * disable invalid-name check by pylint * disable caffe frontend tests * disable mxnet frontend tests * fix stablehlo importer * enable some stablehlo tests * skip tests because mxnet raise AttributeError * use stable sort for `np.argsort` * fix `TypeError: arrays to stack must be passed as a "sequence" type such as list or tuple.` * disable tests because of shape error * remove `get_html_theme_path` because it's deprecated * ignore warnings from sphinx * disable oneflow frontend tests * remove oneflow tutorial * remove debug print
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‎ci/jenkins/docker-images.ini‎

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# This data file is read during when Jenkins runs job to determine docker images.
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[jenkins]
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ci_arm: tlcpack/ci-arm:20240917-153130-9f281758
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ci_cortexm: tlcpack/ci-cortexm:20240917-153130-9f281758
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ci_cpu: tlcpack/ci_cpu:20240917-153130-9f281758
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ci_gpu: tlcpack/ci-gpu:20240917-153130-9f281758
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ci_hexagon: tlcpack/ci-hexagon:20240917-153130-9f281758
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ci_i386: tlcpack/ci-i386:20240917-153130-9f281758
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ci_lint: tlcpack/ci-lint:20240917-153130-9f281758
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ci_minimal: tlcpack/ci-minimal:20240917-153130-9f281758
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ci_riscv: tlcpack/ci-riscv:20240917-153130-9f281758
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ci_wasm: tlcpack/ci-wasm:20240917-153130-9f281758
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ci_arm: tlcpack/ci-arm:20241119-020227-6fc0598c
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ci_cortexm: tlcpack/ci-cortexm:20241119-020227-6fc0598c
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ci_cpu: tlcpack/ci_cpu:20241119-020227-6fc0598c
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ci_gpu: tlcpack/ci-gpu:20241119-020227-6fc0598c
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ci_hexagon: tlcpack/ci-hexagon:20241119-020227-6fc0598c
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ci_i386: tlcpack/ci-i386:20241119-020227-6fc0598c
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ci_lint: tlcpack/ci-lint:20241119-020227-6fc0598c
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ci_minimal: tlcpack/ci-minimal:20241119-020227-6fc0598c
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ci_riscv: tlcpack/ci-riscv:20241119-020227-6fc0598c
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ci_wasm: tlcpack/ci-wasm:20241119-020227-6fc0598c

‎ci/jenkins/unity_jenkinsfile.groovy‎

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@@ -30,14 +30,14 @@
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import org.jenkinsci.plugins.pipeline.modeldefinition.Utils
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// NOTE: these lines are scanned by docker/dev_common.sh. Please update the regex as needed. -->
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ci_lint = 'tlcpack/ci_lint:20240917-153130-9f281758'
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ci_gpu = 'tlcpack/ci_gpu:20240917-153130-9f281758'
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ci_cpu = 'tlcpack/ci_cpu:20240917-153130-9f281758'
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ci_lint = 'tlcpack/ci_lint:20241119-020227-6fc0598c'
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ci_gpu = 'tlcpack/ci_gpu:20241119-020227-6fc0598c'
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ci_cpu = 'tlcpack/ci_cpu:20241119-020227-6fc0598c'
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ci_wasm = 'tlcpack/ci-wasm:v0.72'
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ci_i386 = 'tlcpack/ci-i386:v0.75'
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ci_qemu = 'tlcpack/ci-qemu:v0.11'
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ci_arm = 'tlcpack/ci-arm:v0.08'
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ci_hexagon = 'tlcpack/ci_hexagon:20240917-153130-9f281758'
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ci_hexagon = 'tlcpack/ci_hexagon:20241119-020227-6fc0598c'
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// <--- End of regex-scanned config.
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// Parameters to allow overriding (in Jenkins UI), the images

‎docs/conf.py‎

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@@ -159,7 +159,9 @@ def split_code_and_text_blocks(source_file, return_node, real_func):
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@monkey_patch("sphinx_gallery.gen_rst", "save_rst_example")
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def save_rst_example(example_rst, example_file, time_elapsed, memory_used, gallery_conf, real_func):
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def save_rst_example(
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example_rst, example_file, time_elapsed, memory_used, gallery_conf, language, real_func
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):
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"""Monkey-patch save_rst_example to include the "Open in Colab" button."""
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# The url is the md5 hash of the notebook path.
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python_file=example_fname, ref_name=ref_fname, colab_url=colab_url, button_svg=BUTTON
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)
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with patch("sphinx_gallery.gen_rst.EXAMPLE_HEADER", new_header):
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real_func(example_rst, example_file, time_elapsed, memory_used, gallery_conf)
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real_func(
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example_rst, example_file, time_elapsed, memory_used, gallery_conf, language=language
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)
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INCLUDE_DIRECTIVE_RE = re.compile(r"^([ \t]*)\.\. include::\s*(.+)\n", flags=re.M)
@@ -365,10 +369,7 @@ def jupyter_notebook(script_blocks, gallery_conf, target_dir, real_func):
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on_rtd = os.environ.get("READTHEDOCS", None) == "True"
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# only import rtd theme and set it if want to build docs locally
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if not on_rtd and html_theme == "rtd":
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import sphinx_rtd_theme
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html_theme = "sphinx_rtd_theme"
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html_theme_path = [sphinx_rtd_theme.get_html_theme_path()]
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# Add any paths that contain custom static files (such as style sheets) here,
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# relative to this directory. They are copied after the builtin static files,

‎gallery/how_to/compile_models/from_oneflow.py‎

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This file was deleted.

‎python/tvm/contrib/sparse.py‎

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"""Construct a full matrix and convert it to numpy array."""
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full = _np.zeros(self.shape, self.dtype)
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ridx = _np.diff(self.indptr.numpy())
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ridx = _np.hstack((_np.ones((v,), itype) * i for i, v in enumerate(ridx)))
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ridx = _np.hstack([_np.ones((v,), itype) * i for i, v in enumerate(ridx)])
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full[ridx, self.indices.numpy().astype(itype)] = self.data.numpy()
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return full
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‎python/tvm/relax/expr.py‎

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# This feature is not supported until python 3.10:
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# https://docs.python.org/3.10/whatsnew/3.10.html#pep-613-typealias
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Expr = Union[tvm.ir.RelayExpr]
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Type = Union[tvm.ir.Type]
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Type = Union[tvm.ir.Type] # pylint: disable=invalid-name
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GlobalVar = Union[tvm.ir.GlobalVar]
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‎python/tvm/relax/frontend/stablehlo/stablehlo_translator.py‎

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output : tvm.IRModule
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The result IRModule with entry function "main"
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"""
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from jaxlib import mlir
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from jaxlib.mlir.dialects import stablehlo
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from jax._src.interpreters import mlir as jax_mlir
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if isinstance(stablehlo_module, str):
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# TODO (yongwww): support the serialized bytecode format of StableHLO
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# model using stablehlo.deserialize_portable_artifact(ir) if the python
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# binding is ready
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with mlir.ir.Context() as context:
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stablehlo.register_dialect(context)
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stablehlo_module = mlir.ir.Module.parse(stablehlo_module)
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context = jax_mlir.make_ir_context()
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stablehlo_module = jax_mlir.ir.Module.parse(stablehlo_module, context)
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return StableHLOImporter().from_stablehlo(stablehlo_module, input_info)

‎python/tvm/tir/schedule/schedule.py‎

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# It is a workaround for mypy: https://github.com/python/mypy/issues/7866#issuecomment-549454370
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# This feature is not supported until python 3.10:
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# https://docs.python.org/3.10/whatsnew/3.10.html#pep-613-typealias
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ExprRV = Union[PrimExpr] # A random variable that evaluates to an integer
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# A random variable that evaluates to an integer
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ExprRV = Union[PrimExpr] # pylint: disable=invalid-name
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RAND_VAR_TYPE = Union[ExprRV, BlockRV, LoopRV] # pylint: disable=invalid-name
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‎tests/python/codegen/test_target_codegen_vulkan.py‎

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mod = tvm.IRModule()
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mod["main"] = relay.Function([x], relay.argsort(x))
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x_np = np.random.randint(0, high=10, size=(10,)).astype(dtype)
260-
res_np = np.argsort(x_np)
260+
res_np = np.argsort(x_np, kind="stable")
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check_mod(target, dev, mod, x_np, res_np)
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‎tests/python/codegen/test_target_texture_codegen_opencl.py‎

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@@ -1385,13 +1385,15 @@ class TestConv2dWCHNcCRSKk(BaseConv2DValidator):
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test_func = tvm.testing.parameter(conv2d_1x1_WCHNc_CRSKk)
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@pytest.mark.skip("AttributeError: module 'numpy' has no attribute 'bool' raised from mxnet")
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class TestConv2dNCHWcKCRSk(BaseConv2DValidator):
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input_shapes = tvm.testing.parameter(
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[(1, 32, 56, 56, 4), (32, 128, 1, 1, 4)], [(1, 32, 112, 112, 4), (32, 128, 3, 3, 4)]
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)
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test_func = tvm.testing.parameter(conv2d_NCHWc_KCRSk, conv2d_NCHWc_KCRSk_fp32_acc)
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@pytest.mark.skip("AttributeError: module 'numpy' has no attribute 'bool' raised from mxnet")
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class TestDepthwiseConv2dNCHWcKCRSk(BaseConv2DValidator):
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input_shapes = tvm.testing.parameter([(1, 24, 257, 257, 4), (24, 1, 3, 3, 4)])
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test_func = tvm.testing.parameter(depthwise_conv2d_NCHWc_KCRSk_acc32)

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