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Add dirty prints to check seeds and numpy max on difference platforms
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-3
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3 files changed

+4
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build_tools/azure/test_script.cmd

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@@ -13,4 +13,4 @@ if "%COVERAGE%" == "true" (
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set PYTEST_ARGS=%PYTEST_ARGS% --cov sklearn
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)
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pytest --junitxml=%JUNITXML% --showlocals --durations=20 %PYTEST_ARGS% --pyargs sklearn
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pytest -s --junitxml=%JUNITXML% --showlocals --durations=20 %PYTEST_ARGS% --pyargs sklearn

build_tools/azure/test_script.sh

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@@ -21,7 +21,7 @@ except ImportError:
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python -c "import multiprocessing as mp; print('%d CPUs' % mp.cpu_count())"
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pip list
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TEST_CMD="python -m pytest --showlocals --durations=20 --junitxml=$JUNITXML --pyargs"
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TEST_CMD="python -m pytest -s --showlocals --durations=20 --junitxml=$JUNITXML --pyargs"
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if [[ "$COVERAGE" == "true" ]]; then
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TEST_CMD="$TEST_CMD --cov sklearn"

sklearn/linear_model/stochastic_gradient.py

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@@ -654,7 +654,8 @@ def _fit_multiclass(self, X, y, alpha, C, learning_rate,
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# to non-deterministic behavior
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random_state = check_random_state(self.random_state)
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seeds = random_state.randint(MAX_INT, size=(len(self.classes_)))
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print("Platform max_int: %s" % MAX_INT)
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print("multiclass seeds: %s" % seeds)
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result = Parallel(n_jobs=self.n_jobs, verbose=self.verbose,
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**_joblib_parallel_args(require="sharedmem"))(
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delayed(fit_binary)(self, i, X, y, alpha, C, learning_rate,

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