Merge remote-tracking branch 'remotes/origin/main' into 20231020_maintenance (017856b5) · Commits · IVAS Codec Public Collaboration / IVAS Codec

ci/basop-pages/basop_index.html

+11 −1

Original line number	Diff line number	Diff line
		@@ -7,7 +7,17 @@

		<h2>Regression tracking</h2>

		<li><a href="long_term_regression.html">Long term regression</a></li>
		<ul>
		<li><a href="long_term_mld_enc.html">Long term MLD encoder</a></li>
		<li><a href="long_term_mld_dec.html">Long term MLD decoder</a></li>
		<li><a href="long_term_mld_dec_reject_JBM_BINAURAL_ROOM_REVERB.html">Long term MLD decoder - excluding JBM and BINAURAL_ROOM_REVERB</a></li>
		<li><a href="long_term_max_abs_diff_enc.html">Long term MAX_ABS_DIFF encoder</a></li>
		<li><a href="long_term_max_abs_diff_dec.html">Long term MAX_ABS_DIFF decoder</a></li>
		<li><a href="long_term_max_abs_diff_dec_reject_JBM_BINAURAL_ROOM_REVERB.html">Long term MAX_ABS_DIFF decoder - excluding JBM and BINAURAL_ROOM_REVERB</a></li>

		<li><a href="detect_regressions.html">Detect MLD regressions</a></li>
		<li><a href="detect_regressions.csv">detect_regressions.csv</a></li>
		</ul>

		<h2>Daily long testvector tests</h2>

ci/process_long_term_logs.py

+139 −71

Original line number	Diff line number	Diff line
		#!/usr/bin/env python3

		import os
		import pandas as pd
		import argparse
		import plotly.express as px
		import re
		import plotly.graph_objects as go
		from plotly.subplots import make_subplots

		@@ -23,15 +25,18 @@ def read_csv_files(root_dir):


		def parse_csv_data(csv_data):
		"""keep 'testcase', 'format', 'MLD', 'MAX_ABS_DIFF' and add
		'date' column."""
		cols_to_keep = ["testcase", "format", "MLD", "MAX_ABS_DIFF"]
		"""keep 'testcase', 'format', 'MLD', 'MAX_ABS_DIFF', 'MIN_ODG', 'MIN_SSNR' and add
		'date' and 'job' column."""
		cols_to_keep = ["testcase", "format", "MLD", "MAX_ABS_DIFF", "MIN_ODG", "MIN_SSNR"]
		parsed_data = {}
		for key, df in csv_data.items():
		tmp = key.split("-")
		job = "-".join(tmp[4:-4])
		cols = [col for col in cols_to_keep if col in df.columns]
		date = os.path.basename(os.path.dirname(key))
		new_df = df[cols].copy()
		new_df["date"] = date
		new_df["job"] = job
		parsed_data[key] = new_df

		# concatenate all dataframe in the dictionary
		@@ -39,38 +44,67 @@ def parse_csv_data(csv_data):
		return concat_df


		def plot_data(df, output_filename):
		"""plot max values for 'MLD' and 'MAX_ABS_DIFF' data and save
		def plot_data(df, args):
		"""plot max values for measure and data and save
		to html file."""

		measure = args.measure
		days = args.days

		# Convert 'date' to datetime
		df["date"] = pd.to_datetime(df["date"], errors="coerce")
		df["MLD"] = pd.to_numeric(df["MLD"], errors="coerce")
		df["MAX_ABS_DIFF"] = pd.to_numeric(df["MAX_ABS_DIFF"], errors="coerce")
		df[measure] = pd.to_numeric(df[measure], errors="coerce")

		# Filter out rows older than "days"
		cutoff = df["date"].max() - pd.Timedelta(days=days)
		df = df[df["date"] > cutoff].reset_index(drop=True)

		# Drop rows with NaT and NaN
		clean_df = df.dropna(subset=["date", "MLD", "MAX_ABS_DIFF"])
		df = df.dropna(subset=["date", measure])

		# Filter test cases based on include/reject/match arguments
		if args.include:
		mask = pd.Series(False, index=df.index)
		for tag in args.include:
		mask \|= df["testcase"].str.contains(tag, case=False, na=False)
		df = df[mask]
		if args.reject:
		mask = pd.Series(False, index=df.index)
		for tag in args.reject:
		mask \|= df["testcase"].str.contains(tag, case=False, na=False)
		df = df[~mask]
		if args.match:
		pattern = re.compile(args.match, re.IGNORECASE)
		df = df[df["testcase"].str.contains(pattern, na=False)]

		# Filter jobs based on job-include/job-reject/job-match arguments
		if args.job_include:
		mask = pd.Series(False, index=df.index)
		for tag in args.job_include:
		mask \|= df["job"].str.contains(tag, case=False, na=False)
		df = df[mask]
		if args.job_reject:
		mask = pd.Series(False, index=df.index)
		for tag in args.job_reject:
		mask \|= df["job"].str.contains(tag, case=False, na=False)
		df = df[~mask]
		if args.job_match:
		pattern = re.compile(args.job_match, re.IGNORECASE)
		df = df[df["job"].str.contains(pattern, na=False)]

		# Group by 'format' and 'date' to get rows with max 'MLD' per group
		max_mld = (
		clean_df.groupby(["format", "date"])
		.apply(lambda x: x.loc[x["MLD"].idxmax()])
		.reset_index(drop=True)
		)

		# Group by 'format' and 'date' to get rows with max 'MAX_ABS_DIFF' per
		# group
		max_abs_diff = (
		clean_df.groupby(["format", "date"])
		.apply(lambda x: x.loc[x["MAX_ABS_DIFF"].idxmax()])
		.reset_index(drop=True)
		)
		# Group by 'format' and 'date' to get rows with max 'MLD' per group
		idx = df.groupby(["format", "date"])[measure].idxmax()
		max = df.loc[idx].reset_index(drop=True)
		idx = df.groupby(["format", "date"])[measure].idxmin()
		min = df.loc[idx].reset_index(drop=True)
		mean = df.groupby(["format", "date"])[measure].mean().to_frame("mean").reset_index()

		formats = sorted(clean_df["format"].unique())
		formats = sorted(df["format"].unique())

		fig = make_subplots(
		rows=5,
		cols=2,
		specs=[[{"secondary_y": True}] * 2] * 5,
		subplot_titles=[f"{i}" for i in formats],
		shared_xaxes="columns",
		)
		@@ -79,64 +113,65 @@ def plot_data(df, output_filename):
		row = i // 2 + 1
		col = i % 2 + 1

		data_mld = max_mld[max_mld["format"] == fmt].sort_values("date")
		data_diff = max_abs_diff[max_abs_diff["format"]
		== fmt].sort_values("date")
		if "MIN" in measure:
		data = min[min["format"] == fmt].sort_values("date")
		maxmin_str = "Min"
		else:
		data = max[max["format"] == fmt].sort_values("date")
		maxmin_str = "Max"

		# Add max 'MLD' to primary y-axis
		# Add max measure to plots
		fig.add_trace(
		go.Scatter(
		x=data_mld["date"],
		y=data_mld["MLD"],
		x=data["date"],
		y=data[measure],
		mode="lines+markers",
		name=f" {fmt} - Max MLD",
		name=f"{maxmin_str} {measure}",
		hovertext=[
		f"Testcase: {tc}<br>MLD: {mld:.4f}<br>MAX_ABS_DIFF:"
		f"{abs_diff}<br>Format:"
		f" {format}<br>Date: {date.date()}"
		for tc, mld, abs_diff, format, date in zip(
		data_mld["testcase"],
		data_mld["MLD"],
		data_mld["MAX_ABS_DIFF"],
		data_mld["format"],
		data_mld["date"],
		f"Testcase: {tc}<br>{maxmin_str} {measure}: {value:.4f}"
		f"<br>Job: {job}"
		f"<br>Date: {date.date()}"
		for job, tc, value, date in zip(
		data["job"],
		data["testcase"],
		data[measure],
		data["date"],
		)
		],
		hoverinfo="text",
		marker_color="red",
		showlegend=(i == 0),
		),
		row=row,
		col=col,
		secondary_y=False,
		)

		# Add max 'MAX_ABS_DIFF' to secondary y-axis
		data = mean[mean["format"] == fmt].sort_values("date")

		# Add mean measure to plots
		fig.add_trace(
		go.Scatter(
		x=data_diff["date"],
		y=data_diff["MAX_ABS_DIFF"],
		x=data["date"],
		y=data["mean"],
		mode="lines+markers",
		name=f"{fmt} - Max MAX_ABS_DIFF",
		name=f"Mean {measure}",
		hovertext=[
		f"Testcase: {tc}<br>MLD: {mld:.4f}<br>MAX_ABS_DIFF:"
		f" {abs_diff:.4f}<br>Format:"
		f" {format}<br>Date: {date.date()}"
		for tc, mld, abs_diff, format, date in zip(
		data_diff["testcase"],
		data_diff["MLD"],
		data_diff["MAX_ABS_DIFF"],
		data_diff["format"],
		data_diff["date"],
		f"Mean {measure}: {value:.4f}" f"<br>Date: {date.date()}"
		for value, date in zip(
		data["mean"],
		data["date"],
		)
		],
		hoverinfo="text",
		marker_color="blue",
		showlegend=(i == 0),
		),
		row=row,
		col=col,
		secondary_y=True,
		)

		fig.update_layout(
		title_text="Long-term regression: max MLD and max MAX_ABS_DIFF",
		title_text=f"History: {measure}",
		legend=dict(x=1, y=1, orientation="v"),
		hovermode="x unified",
		)
		@@ -144,21 +179,8 @@ def plot_data(df, output_filename):
		fig.update_xaxes(automargin=True)
		fig.update_yaxes(automargin=True)

		# Update y-axes titles per subplot
		for i in range(10):
		yaxis_num = i * 2 + 1
		yaxis2_num = yaxis_num + 1
		fig["layout"][f"yaxis{yaxis_num}"].update(
		title="Max MLD", titlefont=dict(color="blue"), tickfont=dict(color="blue")
		)
		fig["layout"][f"yaxis{yaxis2_num}"].update(
		title="Max MAX_ABS_DIFF",
		titlefont=dict(color="green"),
		tickfont=dict(color="green"),
		)

		# Save to html
		fig.write_html(output_filename)
		fig.write_html(args.output_filename)


		if __name__ == "__main__":
		@@ -173,8 +195,54 @@ if __name__ == "__main__":
		type=str,
		help="Filename of the generated plot. e.g" ". long_term_regression.html",
		)
		parser.add_argument(
		"--days",
		type=int,
		help="Number of days in history. Default: 30",
		default=30,
		)
		parser.add_argument(
		"--measure",
		type=str,
		help="Measure for analysis: MLD, MAX_ABS_DIFF, MIN_ODG, MIN_SSNR, default: MLD",
		default="MLD",
		)
		parser.add_argument(
		"--include",
		nargs="+",
		type=str,
		help="List of tags to include in testcases",
		)
		parser.add_argument(
		"--reject",
		nargs="+",
		type=str,
		help="List of tags to reject in testcases",
		)
		parser.add_argument(
		"--match",
		type=str,
		help="Regex pattern for selecting testcases",
		)
		parser.add_argument(
		"--job-include",
		nargs="+",
		type=str,
		help="List of tags to include in jobs",
		)
		parser.add_argument(
		"--job-reject",
		nargs="+",
		type=str,
		help="List of tags to reject in jobs",
		)
		parser.add_argument(
		"--job-match",
		type=str,
		help="Regex pattern for selecting jobs",
		)
		args = parser.parse_args()

		csv_data = read_csv_files(args.root_dir)
		data = parse_csv_data(csv_data)
		plot_data(data, args.output_filename)
		plot_data(data, args)

lib_com/ivas_prot.h

+6 −0

Original line number	Diff line number	Diff line
		@@ -1111,11 +1111,17 @@ ivas_error ivas_param_ism_dec_open(
		Decoder_Struct st_ivas / i/o: IVAS decoder structure */
		);

		#ifdef FIX_FLOAT_1526_DIRAC_MEM_LEAK
		void ivas_param_ism_dec_close(
		PARAM_ISM_DEC_HANDLE hParamIsmDec / i/o: decoder ParamISM handle */
		);
		#else
		void ivas_param_ism_dec_close(
		PARAM_ISM_DEC_HANDLE hParamIsmDec, / i/o: decoder ParamISM handle */
		SPAT_PARAM_REND_COMMON_DATA_HANDLE hSpatParamRendCom_out, / i/o: common spatial renderer data */
		const AUDIO_CONFIG output_config /* i : output audio configuration */
		);
		#endif

		void ivas_ism_dec_digest_tc(
		Decoder_Struct st_ivas / i/o: IVAS decoder structure */

lib_com/options.h

+5 −1

Original line number	Diff line number	Diff line
		@@ -161,13 +161,17 @@
		/#define FIX_I4_OL_PITCH/ /* fix open-loop pitch used for EVS core switching */
		#define TMP_1342_WORKAROUND_DEC_FLUSH_BROKEN_IN_SR /* FhG: Temporary workaround for incorrect implementation of decoder flush with split rendering */
		#define NONBE_1122_KEEP_EVS_MODE_UNCHANGED /* FhG: Disables fix for issue 1122 in EVS mode to keep BE tests green. This switch should be removed once the 1122 fix is added to EVS via a CR. */
		#define FIX_FLOAT_1522_LTV_MSAN_QMETADATA_ENC_EC3 /* Nokia: float issue 1522: fix uninit MSAN in EC3 of qmetadata encoding */
		#define FIX_2235_TD_RENDERER_WORD16 /* Eri: For float: small synch with BASOP, removing unnecessary abs. BASOP: Use Word16 in TD renderer without converting to Word32 */
		#define FIX_FLOAT_1526_DIRAC_MEM_LEAK /* FhG: potential memory leak in DirAC handles in case of format switching */
		#define ALIGN_ACELP_CORE /* VA: align ACELP core functions with BASOP */

		/* #################### End BE switches ################################## */

		/* #################### Start NON-BE switches ############################ */
		/* any switch which is non-be wrt. TS 26.258 V3.0 */

		#define FIX_2432_ISM_SPIKES_16KHZ /* VA: basop issue 2432: fix spikes in ISM decoding at 16kHz output sampling rate */

		/* ##################### End NON-BE switches ########################### */

		/* ################## End MAINTENANCE switches ######################### */

lib_com/prot.h

+11 −7

Original line number	Diff line number	Diff line
		@@ -2336,7 +2336,9 @@ void MDCT_classifier_reset(
		ivas_error acelp_core_enc(
		Encoder_State st, / i/o: encoder state structure */
		const float inp[], /* i : input signal of the current frame */
		#ifndef ALIGN_ACELP_CORE
		const float ener, /* i : residual energy from Levinson-Durbin */
		#endif
		float A[NB_SUBFR16k * ( M + 1 )], /* i : A(z) unquantized for the 4 subframes */
		float Aw[NB_SUBFR16k * ( M + 1 )], /* i : weighted A(z) unquant. for subframes */
		const float epsP[M + 1], /* i : LP prediction errors */
		@@ -3029,7 +3031,9 @@ void CNG_enc(
		Encoder_State st, / i/o: State structure */
		float Aq[], /* o : LP coefficients */
		const float speech, / i : pointer to current frame input speech buffer */
		#ifndef ALIGN_ACELP_CORE
		float enr, /* i : frame energy output from Levinson recursion */
		#endif
		const float lsp_mid, / i : mid frame LSPs */
		float lsp_new, / i/o: current frame LSPs */
		float lsf_new, / i/o: current frame LSFs */