[DebuggerV2] Enable debug_v2_ops_test & debug_events_writer_test on Windows
- A test in debug_v2_ops_test previously called `np.power(2, 53)` without specifying dtype. As a result, the output had the int32 dtype on Windows and caused overflowing. This apparently does not happen on Linux or Mac. - This CL fixes that by explicitly specifying `dtype=np.int64` in the call. - In debug_events_write.cc, check for whether the DebugEventsWriter instance is initialized and return early if not so. - This resolves a directory-not-empty test failure in debug_events_writer_test on Windows This is a step towards fixing #43608 PiperOrigin-RevId: 349569528 Change-Id: I8112f8faebe662542e80c03d5d95e8e089446fe8
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@ -783,7 +783,6 @@ tf_cc_test(
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"//conditions:default": [],
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"//conditions:default": [],
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}),
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}),
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linkstatic = tf_kernel_tests_linkstatic(),
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linkstatic = tf_kernel_tests_linkstatic(),
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tags = ["no_windows"], # b/150411480
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deps = [
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deps = [
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"//tensorflow/core:framework",
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"//tensorflow/core:framework",
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"//tensorflow/core:lib",
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"//tensorflow/core:lib",
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@ -403,6 +403,13 @@ string DebugEventsWriter::FileName(DebugEventFileType type) {
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}
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}
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Status DebugEventsWriter::Close() {
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Status DebugEventsWriter::Close() {
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{
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mutex_lock l(initialization_mu_);
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if (!is_initialized_) {
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return Status::OK();
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}
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}
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std::vector<string> failed_to_close_files;
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std::vector<string> failed_to_close_files;
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if (metadata_writer_ != nullptr) {
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if (metadata_writer_ != nullptr) {
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@ -776,9 +776,6 @@ cuda_py_test(
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size = "medium",
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size = "medium",
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srcs = ["lib/debug_v2_ops_test.py"],
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srcs = ["lib/debug_v2_ops_test.py"],
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python_version = "PY3",
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python_version = "PY3",
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tags = [
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"no_windows", # b/142475891
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],
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deps = [
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deps = [
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":debug_events_reader",
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":debug_events_reader",
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":debug_events_writer",
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":debug_events_writer",
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@ -339,7 +339,7 @@ class DebugNumericSummaryV2Test(test_util.TensorFlowTestCase):
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debug_event_pb2.TensorDebugMode.SHAPE,
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debug_event_pb2.TensorDebugMode.SHAPE,
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]
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]
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# Maximum allowed tensor_id
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# Maximum allowed tensor_id
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tensor_id = np.power(2, 53)
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tensor_id = np.power(2, 53, dtype=np.int64)
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for mode in modes:
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for mode in modes:
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self.evaluate(
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self.evaluate(
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gen_debug_ops.debug_numeric_summary_v2(
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gen_debug_ops.debug_numeric_summary_v2(
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