AVh6dZddlZddlmZddlmZddlmZ ddl m Z ddl m Z ddl m Zdd l mZdd l mZdd lmZdd lmZdd lmZedgee j,Ze j.Zedd"dZedgdZedgdZeddZeddZeddZeddZeddZed d!Z y)#zTesting.N)mock) test_util) googletest)assert_equal_graph_def)create_local_cluster)TensorFlowTestCase)gpu_device_name)is_gpu_available)compute_gradient_error)compute_gradient) tf_exportz test.mock)v1z test.maincTtjtj|S)zRuns all unit tests.) _test_utilInstallStackTraceHandler _googletestmain)argvs O/home/dcms/DCMS/lib/python3.12/site-packages/tensorflow/python/platform/test.pyrr1s! %%'   $ ztest.get_temp_dirc*tjS)aReturns a temporary directory for use during tests. There is no need to delete the directory after the test. @compatibility(TF2) This function is removed in TF2. Please use `TestCase.get_temp_dir` instead in a test case. Outside of a unit test, obtain a temporary directory through Python's `tempfile` module. @end_compatibility Returns: The temporary directory. )r GetTempDirrr get_temp_dirr8s    !!rztest.test_src_dir_pathc,tj|S)zCreates an absolute test srcdir path given a relative path. Args: relative_path: a path relative to tensorflow root. e.g. "core/platform". Returns: An absolute path to the linked in runfiles. )rtest_src_dir_path) relative_paths rrrKs  & &} 55rztest.is_built_with_cudac*tjS)a%Returns whether TensorFlow was built with CUDA (GPU) support. This method should only be used in tests written with `tf.test.TestCase`. A typical usage is to skip tests that should only run with CUDA (GPU). >>> class MyTest(tf.test.TestCase): ... ... def test_add_on_gpu(self): ... if not tf.test.is_built_with_cuda(): ... self.skipTest("test is only applicable on GPU") ... ... with tf.device("GPU:0"): ... self.assertEqual(tf.math.add(1.0, 2.0), 3.0) TensorFlow official binary is built with CUDA. )rIsGoogleCudaEnabledrrris_built_with_cudar Ys$  ' ' ))rztest.is_built_with_rocmc*tjS)a)Returns whether TensorFlow was built with ROCm (GPU) support. This method should only be used in tests written with `tf.test.TestCase`. A typical usage is to skip tests that should only run with ROCm (GPU). >>> class MyTest(tf.test.TestCase): ... ... def test_add_on_gpu(self): ... if not tf.test.is_built_with_rocm(): ... self.skipTest("test is only applicable on GPU") ... ... with tf.device("GPU:0"): ... self.assertEqual(tf.math.add(1.0, 2.0), 3.0) TensorFlow official binary is NOT built with ROCm. )rIsBuiltWithROCmrrris_built_with_rocmr#ns$  # # %%rztest.disable_with_predicatecfd}|S)z"Disables the test if pred is true.cHtjfd}|S)NcNr|jy|g|i|SN)skipTest)selfargskwargsfuncpred skip_messages rwrapper_disable_with_predicatezhdisable_with_predicate..decorator_disable_with_predicate..wrapper_disable_with_predicates)  l#D*4*6**r) functoolswraps)r,r/r-r.s` r decorator_disable_with_predicatez@disable_with_predicate..decorator_disable_with_predicates&__T++ *)rr)r-r.r2s`` rdisable_with_predicater3s * *)rztest.is_built_with_gpu_supportc.txs tS)a9Returns whether TensorFlow was built with GPU (CUDA or ROCm) support. 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A typical usage is to skip tests that should only run with XLA. >>> class MyTest(tf.test.TestCase): ... ... def test_add_on_xla(self): ... if not tf.test.is_built_with_xla(): ... self.skipTest("test is only applicable on XLA") ... @tf.function(jit_compile=True) ... def add(x, y): ... return tf.math.add(x, y) ... ... self.assertEqual(add(tf.ones(()), tf.ones(())), 2.0) TensorFlow official binary is built with XLA. )rIsBuiltWithXLArrris_built_with_xlar8s*  " " $$rztest.is_cpu_target_availablec,tj|S)aIndicates whether TensorFlow was built with support for a given CPU target. Args: target: The name of the CPU target whose support to check for. Returns: A boolean indicating whether TensorFlow was built with support for the given CPU target. This method should only be used in tests written with `tf.test.TestCase`. A typical usage is to skip tests that should only run with a given target. >>> class MyTest(tf.test.TestCase): ... ... def test_add_on_aarch64(self): ... if not tf.test.is_cpu_target_available('aarch64'): ... self.skipTest("test is only applicable on AArch64") ... @tf.function(jit_compile=True) ... def add(x, y): ... return tf.math.add(x, y) ... ... self.assertEqual(add(tf.ones(()), tf.ones(())), 2.0) )rIsCPUTargetAvailable)targets ris_cpu_target_availabler<s4  ( ( 00rr')!__doc__r0unittestrtensorflow.python.frameworkrrtensorflow.python.platformrr%tensorflow.python.framework.test_utilrrrTestCaser r &tensorflow.python.ops.gradient_checkerr r tensorflow.python.util.tf_exportr BenchmarkStubOutForTestingrrrr r#r3r5r8r<rrrrGsQ @@IFPABIC7 k]D!  ! !  11 ;   "#$"%"$ '() 6* 6 $%*&*( $%&&&( ()***" +,6-6( #$%%%. )*1+1r