fix MLD corridor re-generation (f732563f) · Commits · IVAS Codec Public Collaboration / IVAS Codec

scripts/ivas_conformance/runConformance.py

+83 −68

Original line number	Diff line number	Diff line
		@@ -967,21 +967,25 @@ class MLDConformance:
		errorDetails,
		executedCommand,
		) in pool.imap_unordered(self.analyseOneCommandFromTuple, args):
		if self.args.verbose:
		if runStatus == "OK":
		if not analysisResult:
		print(
		f"{testPrefix} Running test: {pyTestsTag} ... {runStatus}",
		f"{testPrefix} Analyzing test: {pyTestsTag} ... Command executed successfully but MLD analysis failed!",
		flush=True,
		)
		if self.args.verbose and executedCommand:
		else:
		print(
		f"{testPrefix} Executing command: {executedCommand}",
		f"{testPrefix} Analyzing test: {pyTestsTag} ... {analysisResult}",
		flush=True,
		)
		if runStatus == "OK":
		else:
		print(
		f"{testPrefix} Analyzing test: {analysisResult}",
		f"{testPrefix} Analyzing test: {pyTestsTag} ... {runStatus}",
		flush=True,
		)
		elif errorDetails:

		if errorDetails:
		cmd, err_output = errorDetails
		print(f"{testPrefix} Failed command: {cmd}", flush=True)
		if err_output:
		@@ -1000,21 +1004,25 @@ class MLDConformance:
		errorDetails,
		executedCommand,
		) = self.analyseOneCommand(tag, pyTestsTag, idx, self.totalTests)
		if self.args.verbose:
		if runStatus == "OK":
		if not analysisResult:
		print(
		f"{testPrefix} Running test: {pyTestsTag} ... {runStatus}",
		f"{testPrefix} Analyzing test: {pyTestsTag} ... Command executed successfully but MLD analysis failed!",
		flush=True,
		)
		if self.args.verbose and executedCommand:
		else:
		print(
		f"{testPrefix} Executing command: {executedCommand}",
		f"{testPrefix} Analyzing test: {pyTestsTag} ... {analysisResult}",
		flush=True,
		)
		if runStatus == "OK":
		else:
		print(
		f"{testPrefix} Analyzing test: {analysisResult}",
		f"{testPrefix} Analyzing test: {pyTestsTag} ... {runStatus}",
		flush=True,
		)
		elif errorDetails:

		if errorDetails:
		cmd, err_output = errorDetails
		print(f"{testPrefix} Failed command: {cmd}", flush=True)
		if err_output:
		@@ -1267,38 +1275,45 @@ class MLDConformance:
		print(f"<{tag}> PASSED BE TEST")

		def computeCorridor(self, mldRefWithTags, mldCutWithTags, tag, threshold=0.1):
		mldDict = dict[str, list]()
		failed = False

		#intersection, indRef, indDut = np.intersect1d(
		# mldRefWithTags["pyTestTag"],
		# mldCutWithTags["pyTestTag"],
		# assume_unique=True,
		# return_indices=True,
		#)

		indRef = np.argsort(mldRefWithTags["pyTestTag"])
		indDut = np.argsort(mldCutWithTags["pyTestTag"])
		intersection = mldRefWithTags["pyTestTag"][indRef]

		refTags = mldRefWithTags["pyTestTag"][indRef]
		dutTags = mldCutWithTags["pyTestTag"][indDut]
		refMLD = mldRefWithTags["MLD"][indRef]
		dutMLD = mldCutWithTags["MLD"][indDut]

		diff = dutMLD - refMLD
		same_shape = refMLD.shape == dutMLD.shape
		same_tags = same_shape and np.array_equal(refTags, dutTags)

		if diff.max() > threshold:
		print(
		f"\033[91mMLD Corridor failed for {tag} with max MLD diff of {diff.max()} \033[00m"
		)
		if same_tags:
		diff = dutMLD - refMLD
		maxDiff = float(diff.max()) if diff.size else 0.0
		corridor_failed = maxDiff > threshold
		maxMLD = np.maximum(dutMLD, refMLD)
		mldWithTags = np.column_stack(
		(
		maxMLD,
		intersection,
		mldWithTags = np.column_stack((maxMLD, refTags))
		else:
		# For any mismatch, emit mld_ref2 directly from DUT values/tags.
		maxDiff = float("nan")
		mldWithTags = np.column_stack((dutMLD, dutTags))
		corridor_failed = True

		if corridor_failed:
		mismatch_reason = []
		if not same_shape:
		mismatch_reason.append(
		f"shape mismatch REF={refMLD.shape}, DUT={dutMLD.shape}"
		)
		if same_shape and not same_tags:
		mismatch_reason.append("pyTestTag mismatch")
		mismatch_suffix = (
		f" ({'; '.join(mismatch_reason)})" if mismatch_reason else ""
		)
		print(
		f"\033[91mMLD Corridor failed for {tag} with max MLD diff of {maxDiff}{mismatch_suffix} \033[00m"
		)
		new_mld_dir = os.path.join(
		self.testvDir, "mld_ref2")
		self.testvDir, "mld_ref2"
		)
		if not os.path.exists(new_mld_dir):
		os.makedirs(new_mld_dir, exist_ok=True)

		@@ -1309,7 +1324,7 @@ class MLDConformance:
		np.savetxt(f, mldWithTags, fmt="%s", delimiter=",")
		else:
		print(
		f"\033[92mMLD Corridor passed for {tag} with max MLD diff of {diff.max()} \033[00m"
		f"\033[92mMLD Corridor passed for {tag} with max MLD diff of {maxDiff} \033[00m"
		)

		def doAnalysis(self, selectTag="all", corridor=False):