change docker install script

update test script to use pytest instead of nose

fix mybfloat16

do

save

fix test

fix test

Author: MarisaKirisame

conda/tvm/meta.yaml

@@ -50,12 +50,12 @@ test:
     - topi
     - nnvm
   requires:
-    - nose
+    - pytest
     - scipy
   source_files:
     - tests/python
   commands:
-    - python -m nose -v tests/python/integration
+    - python -m pytest -v tests/python/integration
 
 about:
   home: https://github.com/dmlc/tvm

docker/Dockerfile.conda_cpu

@@ -30,9 +30,9 @@ RUN curl -o ~/miniconda.sh -O https://repo.continuum.io/miniconda/Miniconda3-lat
 # Cache some of the packages for the builds
 RUN /opt/conda/bin/conda install --download-only cmake make zlib && \
     /opt/conda/bin/conda install --download-only -c numba llvmdev=8.0.0 && \
-    /opt/conda/bin/conda create -n py35 --download-only nose scipy numpy=1.11 cython decorator python=3.5 && \
-    /opt/conda/bin/conda create -n py36 --download-only nose scipy numpy=1.11 cython decorator python=3.6 && \
-    /opt/conda/bin/conda create -n py37 --download-only nose scipy numpy=1.11 cython decorator python=3.7
+    /opt/conda/bin/conda create -n py35 --download-only pytest scipy numpy=1.11 cython decorator python=3.5 && \
+    /opt/conda/bin/conda create -n py36 --download-only pytest scipy numpy=1.11 cython decorator python=3.6 && \
+    /opt/conda/bin/conda create -n py37 --download-only pytest scipy numpy=1.11 cython decorator python=3.7
 
 ENV PATH /opt/conda/bin:$PATH
 ENV CONDA_BLD_PATH /tmp

docker/Dockerfile.demo_cpu

@@ -26,7 +26,7 @@ RUN bash /install/ubuntu_install_core.sh
 
 # Python: basic dependencies
 RUN apt-get update && apt-get install -y python3-dev python3-pip
-RUN pip3 install numpy nose-timer cython decorator scipy
+RUN pip3 install numpy pytest cython decorator scipy
 
 # LLVM
 RUN echo deb http://apt.llvm.org/xenial/ llvm-toolchain-xenial-6.0 main \

docker/Dockerfile.demo_gpu

@@ -26,7 +26,7 @@ RUN bash /install/ubuntu_install_core.sh
 
 # Python: basic dependencies
 RUN apt-get update && apt-get install -y python3-dev python3-pip
-RUN pip3 install numpy nose-timer cython decorator scipy
+RUN pip3 install numpy pytest cython decorator scipy
 
 # LLVM
 RUN echo deb http://apt.llvm.org/xenial/ llvm-toolchain-xenial-6.0 main \

docker/Dockerfile.demo_opencl

@@ -42,7 +42,7 @@ RUN apt-get install -y libopenblas-dev
 
 RUN echo "Installing Python"
 RUN apt-get install -y python3-dev python3-pip
-RUN pip3 install setuptools numpy nose-timer cython decorator scipy tornado psutil xgboost
+RUN pip3 install setuptools numpy pytest cython decorator scipy tornado psutil xgboost
 
 RUN echo "Installing Jupyter notebook"
 RUN pip3 install matplotlib Image Pillow jupyter[notebook]

docker/install/ubuntu_install_python_package.sh

@@ -6,9 +6,9 @@
 # to you under the Apache License, Version 2.0 (the
 # "License"); you may not use this file except in compliance
 # with the License.  You may obtain a copy of the License at
-# 
+#
 #   http://www.apache.org/licenses/LICENSE-2.0
-# 
+#
 # Unless required by applicable law or agreed to in writing,
 # software distributed under the License is distributed on an
 # "AS IS" BASIS, WITHOUT WARRANTIES OR CONDITIONS OF ANY
@@ -21,5 +21,4 @@ set -u
 set -o pipefail
 
 # install libraries for python package on ubuntu
-pip2 install nose pylint==1.9.4 six numpy nose-timer cython decorator scipy tornado typing antlr4-python2-runtime attrs packaging
-pip3 install nose pylint==1.9.4 six numpy nose-timer cython decorator scipy tornado typed_ast pytest mypy orderedset antlr4-python3-runtime attrs requests Pillow packaging
+pip3 install pylint==1.9.4 six numpy pytest cython decorator scipy tornado typed_ast pytest mypy orderedset antlr4-python3-runtime attrs requests Pillow packaging

docs/contribute/pull_request.rst

@@ -96,7 +96,7 @@ Necessary dependencies:
 
 .. code:: bash
 
-  pip install --user nose Cython
+  pip install --user pytest Cython
 
 If you want to run all tests:
 
@@ -118,4 +118,4 @@ If you want to run a single test:
   export PYTHONPATH=python:topi/python
   rm -rf python/tvm/*.pyc python/tvm/*/*.pyc python/tvm/*/*/*.pyc
 
-  TVM_FFI=ctypes python -m nose -v tests/python/unittest/test_pass_storage_rewrite.py
+  TVM_FFI=ctypes python -m pytest -v tests/python/unittest/test_pass_storage_rewrite.py

nnvm/tests/python/frontend/mxnet/test_forward.py

@@ -31,7 +31,7 @@
 
 def verify_mxnet_frontend_impl(mx_symbol, data_shape=(1, 3, 224, 224), out_shape=(1, 1000),
                                gluon_impl=False, name=None, dtype='float32'):
-    """Use name different from test to avoid let nose pick it up"""
+    """Use name different from test to avoid pytest picking it up"""
     if gluon_impl:
         def get_gluon_output(name, x):
             net = vision.get_model(name)

tests/python/contrib/test_mxnet_bridge.py

@@ -17,7 +17,7 @@
 def mxnet_check():
     """This is a simple test function for MXNet bridge
 
-    It is not included as nosetests, because of its dependency on mxnet
+    It is not included as pytests, because of its dependency on mxnet
 
     User can directly run this script to verify correctness.
     """

tests/python/contrib/test_nnpack.py

@@ -18,7 +18,7 @@
 import numpy as np
 import scipy.signal
 from tvm.contrib import nnpack
-from nose import SkipTest
+import pytest
 
 
 def test_fully_connected_inference():
@@ -34,11 +34,11 @@ def test_fully_connected_inference():
 
     def verify(target="llvm"):
         if not tvm.module.enabled(target):
-            raise SkipTest("skip because %s is not enabled..." % target)
+            pytest.skip("%s is not enabled..." % target)
         if not tvm.get_global_func("tvm.contrib.nnpack.fully_connected_inference", True):
-            raise SkipTest("skip because extern function is not available")
+            pytest.skip("extern function is not available")
         if not nnpack.is_available():
-            raise SkipTest("skip because nnpack is not available")
+            pytest.skip("nnpack is not available")
 
         ctx = tvm.cpu(0)
         f = tvm.build(s, [A, B, D, bias], target)
@@ -112,11 +112,11 @@ def verify(target="llvm",
                algorithm=nnpack.ConvolutionAlgorithm.AUTO,
                with_bias=True):
         if not tvm.module.enabled(target):
-            raise SkipTest("skip because %s is not enabled..." % target)
+            pytest.skip("%s is not enabled..." % target)
         if not tvm.get_global_func("tvm.contrib.nnpack.fully_connected_inference", True):
-            raise SkipTest("skip because extern function is not available")
+            pytest.skip("extern function is not available")
         if not nnpack.is_available():
-            raise SkipTest("skip because nnpack is not available")
+            pytest.skip("nnpack is not available")
 
         ctx = tvm.cpu(0)
         output = nnpack.convolution_inference(
@@ -174,11 +174,11 @@ def verify(target="llvm",
                algorithm=nnpack.ConvolutionAlgorithm.AUTO,
                with_bias=True):
         if not tvm.module.enabled(target):
-            raise SkipTest("skip because %s is not enabled..." % target)
+            pytest.skip("%s is not enabled..." % target)
         if not tvm.get_global_func("tvm.contrib.nnpack.fully_connected_inference", True):
-            raise SkipTest("skip because extern function is not available")
+            pytest.skip("extern function is not available")
         if not nnpack.is_available():
-            raise SkipTest("skip because nnpack is not available")
+            pytest.skip("nnpack is not available")
 
         ctx = tvm.cpu(0)
         transformed_kernel = nnpack.convolution_inference_weight_transform(
@@ -209,5 +209,4 @@ def verify(target="llvm",
 
 
 if __name__ == "__main__":
-    import nose
-    nose.runmodule()
+    pytest.main()

tests/python/contrib/test_rpc_proxy.py

@@ -24,7 +24,7 @@
 def rpc_proxy_check():
     """This is a simple test function for RPC Proxy
 
-    It is not included as nosetests, because:
+    It is not included as pytests, because:
     - It depends on tornado
     - It relies on the fact that Proxy starts before client and server connects,
       which is often the case but not always

tests/python/frontend/mxnet/test_forward.py

@@ -34,7 +34,7 @@ def verify_mxnet_frontend_impl(mx_symbol,
                                gluon_impl=False,
                                name=None,
                                dtype='float32'):
-    """Use name different from test to avoid let nose pick it up"""
+    """Use name different from test to avoid pytest picking it up"""
     if gluon_impl:
         def get_gluon_output(name, x):
             net = vision.get_model(name)

tests/python/integration/test_winograd_nnpack.py

@@ -23,7 +23,7 @@
 import topi
 import topi.testing
 from topi.util import get_const_tuple
-from nose import SkipTest
+from pytest import skip
 
 
 def verify_conv2d_nchw(batch, in_channel, in_size, num_filter, kernel, stride, padding, dilation=1, add_bias=False, add_relu=False,
@@ -60,7 +60,7 @@ def get_ref_data():
     def check_device(device):
         ctx = tvm.context(device, 0)
         if not ctx.exist:
-            raise SkipTest("Skip because %s is not enabled" % device)
+            skip("s is not enabled" % device)
         print("Running on target: %s" % device)
         with tvm.target.create(device):
             C = topi.nn.conv2d(A, W, stride, padding, dilation, layout='NCHW', out_dtype=dtype)
@@ -99,10 +99,10 @@ def _query_inside(self, target, workload):
 
 def test_conv2d_nchw():
     if not tvm.get_global_func("tvm.contrib.nnpack.convolution_inference_without_weight_transform", True):
-        raise SkipTest("skip because extern function is not available")
+        skip("extern function is not available")
 
     if not nnpack.is_available():
-        raise SkipTest("skip because nnpack is not available")
+        skip("nnpack is not available")
 
     devices = ['llvm -device=arm_cpu']
     autotvm.DispatchContext.current.silent = True
@@ -139,5 +139,5 @@ def test_conv2d_nchw():
 
 
 if __name__ == "__main__":
-    import nose
-    nose.runmodule()
+    import pytest
+    pytest.main()

tests/python/relay/test_ir_parser.py

@@ -17,11 +17,11 @@
 import tvm
 from tvm import relay
 from tvm.relay.analysis import alpha_equal, assert_alpha_equal
-from nose.tools import nottest, raises
+import pytest
 from numpy import isclose
 from typing import Union
 from functools import wraps
-raises_parse_error = raises(tvm._ffi.base.TVMError)
+raises_parse_error = pytest.mark.xfail(raises=tvm._ffi.base.TVMError)
 
 SEMVER = "v0.0.3"
 
@@ -177,7 +177,7 @@ def test_op_assoc():
     assert alpha_equal(parse_text("1 == 1 < 1 + 1 * 1"), parse_text("1 == (1 < (1 + (1 * 1)))"))
 
 
-@nottest
+@pytest.mark.skip
 def test_vars():
     # temp vars won't work b/c they start with a digit
     # # temp var
@@ -529,11 +529,6 @@ def test_builtin_types():
         parse_text("let %_ : {} = (); ()".format(builtin_type))
 
 
-@nottest
-def test_call_type():
-    assert False
-
-
 def test_tensor_type():
     assert parses_as(
         "let %_ : Tensor[(), float32] = (); ()",

tests/python/relay/test_op_level3.py

@@ -17,7 +17,7 @@
 """ Support level3 operator test cases.
 """
 import numpy as np
-from nose.tools import raises
+import pytest
 import tvm
 from tvm import relay
 from tvm.relay import create_executor, transform
@@ -220,8 +220,7 @@ def test_squeeze_infer_type():
     assert yy.checked_type == relay.TensorType(
         (4,), "float32")
 
-
-@raises(tvm._ffi.base.TVMError)
+@pytest.mark.xfail(raises=tvm._ffi.base.TVMError)
 def test_squeeze_bad_axes_infer_type():
     n, t, d = 1, 4, 1
     x = relay.var("x", relay.TensorType((n, t, d), "float32"))

tests/python/relay/test_pass_check_kind.py

@@ -17,8 +17,7 @@
 import tvm
 from tvm import relay
 from tvm.relay.analysis import check_kind
-from nose.tools import raises
-
+import pytest
 
 def test_typevar_kind():
     # returns the same kind
@@ -111,7 +110,7 @@ def test_typecall_kind():
     assert check_kind(call, new_mod) == relay.Kind.Type
 
 
-@raises(tvm._ffi.base.TVMError)
+@pytest.mark.xfail(raises=tvm._ffi.base.TVMError)
 def test_invalid_tuple_kind():
     tp1 = relay.TypeVar('tp1', relay.Kind.Shape)
     tp2 = relay.TypeVar('tp2', relay.Kind.BaseType)
@@ -122,7 +121,7 @@ def test_invalid_tuple_kind():
     check_kind(tup_ty)
 
 
-@raises(tvm._ffi.base.TVMError)
+@pytest.mark.xfail(raises=tvm._ffi.base.TVMError)
 def test_invalid_func_kind():
     tp1 = relay.TypeVar('tp1', relay.Kind.Shape)
     tp2 = relay.TypeVar('tp2', relay.Kind.BaseType)
@@ -137,14 +136,14 @@ def test_invalid_func_kind():
     check_kind(tf)
 
 
-@raises(tvm._ffi.base.TVMError)
+@pytest.mark.xfail(raises=tvm._ffi.base.TVMError)
 def test_invalid_ref_kind():
     tp = relay.TypeVar('tp', relay.Kind.Shape)
     rt = relay.RefType(tp)
     check_kind(rt)
 
 
-@raises(tvm._ffi.base.TVMError)
+@pytest.mark.xfail(raises=tvm._ffi.base.TVMError)
 def test_invalid_relation_kind():
     tp1 = relay.TypeVar('tp1', relay.Kind.Shape)
     tp2 = relay.TypeVar('tp2', relay.Kind.BaseType)
@@ -156,14 +155,14 @@ def test_invalid_relation_kind():
     check_kind(tr)
 
 
-@raises(tvm._ffi.base.TVMError)
+@pytest.mark.xfail(raises=tvm._ffi.base.TVMError)
 def test_typecall_invalid_callee():
     # global type var must be an ADT handle
     gtv = relay.GlobalTypeVar('v1', relay.Kind.Type)
     check_kind(relay.TypeCall(gtv, []))
 
 
-@raises(tvm._ffi.base.TVMError)
+@pytest.mark.xfail(raises=tvm._ffi.base.TVMError)
 def test_typecall_invalid_args():
     # args must all be type kind
     mod = relay.Module()
@@ -174,7 +173,7 @@ def test_typecall_invalid_args():
     check_kind(relay.TypeCall(gtv, [data]))
 
 
-@raises(tvm._ffi.base.TVMError)
+@pytest.mark.xfail(raises=tvm._ffi.base.TVMError)
 def test_typecall_invalid_num_args():
     mod = relay.Module()
     gtv = relay.GlobalTypeVar('v1')
@@ -184,7 +183,7 @@ def test_typecall_invalid_num_args():
     check_kind(relay.TypeCall(gtv, []))
 
 
-@raises(tvm._ffi.base.TVMError)
+@pytest.mark.xfail(raises=tvm._ffi.base.TVMError)
 def test_func_with_invalid_ret_type():
     tp1 = relay.TypeVar('tp1', relay.Kind.Type)
     tp2 = relay.TypeVar('tp2', relay.Kind.Shape)
@@ -193,7 +192,7 @@ def test_func_with_invalid_ret_type():
     check_kind(tf)
 
 
-@raises(tvm._ffi.base.TVMError)
+@pytest.mark.xfail(raises=tvm._ffi.base.TVMError)
 def test_func_with_invalid_arg_types():
     tp1 = relay.TypeVar('tp1', relay.Kind.Shape)
     tp2 = relay.TypeVar('tp2', relay.Kind.Type)
@@ -202,7 +201,7 @@ def test_func_with_invalid_arg_types():
     check_kind(tf)
 
 
-@raises(tvm._ffi.base.TVMError)
+@pytest.mark.xfail(raises=tvm._ffi.base.TVMError)
 def test_func_with_invalid_tuple():
     tp1 = relay.TypeVar('tp1', relay.Kind.Shape)
 
@@ -212,7 +211,7 @@ def test_func_with_invalid_tuple():
     check_kind(tf)
 
 
-@raises(tvm._ffi.base.TVMError)
+@pytest.mark.xfail(raises=tvm._ffi.base.TVMError)
 def test_func_with_invalid_relation():
     tp1 = relay.TypeVar('tp1', relay.Kind.Type)
     tp2 = relay.TypeVar('tp2', relay.Kind.Shape)
@@ -225,7 +224,7 @@ def test_func_with_invalid_relation():
     check_kind(tf)
 
 
-@raises(tvm._ffi.base.TVMError)
+@pytest.mark.xfail(raises=tvm._ffi.base.TVMError)
 def test_tuple_with_invalid_func():
     tensor_type = relay.TensorType(tvm.convert([1, 2, 3]), 'float32')