Upload synthesizer/utils/plot.py with huggingface_hub

synthesizer/utils/plot.py

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+import matplotlib
+matplotlib.use("Agg")
+import matplotlib.pyplot as plt
+import numpy as np
+
+
+def split_title_line(title_text, max_words=5):
+	"""
+	A function that splits any string based on specific character
+	(returning it with the string), with maximum number of words on it
+	"""
+	seq = title_text.split()
+	return "\n".join([" ".join(seq[i:i + max_words]) for i in range(0, len(seq), max_words)])
+
+def plot_alignment(alignment, path, title=None, split_title=False, max_len=None):
+	if max_len is not None:
+		alignment = alignment[:, :max_len]
+
+	fig = plt.figure(figsize=(8, 6))
+	ax = fig.add_subplot(111)
+
+	im = ax.imshow(
+		alignment,
+		aspect="auto",
+		origin="lower",
+		interpolation="none")
+	fig.colorbar(im, ax=ax)
+	xlabel = "Decoder timestep"
+
+	if split_title:
+		title = split_title_line(title)
+
+	plt.xlabel(xlabel)
+	plt.title(title)
+	plt.ylabel("Encoder timestep")
+	plt.tight_layout()
+	plt.savefig(path, format="png")
+	plt.close()
+
+
+def plot_spectrogram(pred_spectrogram, path, title=None, split_title=False, target_spectrogram=None, max_len=None, auto_aspect=False):
+	if max_len is not None:
+		target_spectrogram = target_spectrogram[:max_len]
+		pred_spectrogram = pred_spectrogram[:max_len]
+
+	if split_title:
+		title = split_title_line(title)
+
+	fig = plt.figure(figsize=(10, 8))
+	# Set common labels
+	fig.text(0.5, 0.18, title, horizontalalignment="center", fontsize=16)
+
+	#target spectrogram subplot
+	if target_spectrogram is not None:
+		ax1 = fig.add_subplot(311)
+		ax2 = fig.add_subplot(312)
+
+		if auto_aspect:
+			im = ax1.imshow(np.rot90(target_spectrogram), aspect="auto", interpolation="none")
+		else:
+			im = ax1.imshow(np.rot90(target_spectrogram), interpolation="none")
+		ax1.set_title("Target Mel-Spectrogram")
+		fig.colorbar(mappable=im, shrink=0.65, orientation="horizontal", ax=ax1)
+		ax2.set_title("Predicted Mel-Spectrogram")
+	else:
+		ax2 = fig.add_subplot(211)
+
+	if auto_aspect:
+		im = ax2.imshow(np.rot90(pred_spectrogram), aspect="auto", interpolation="none")
+	else:
+		im = ax2.imshow(np.rot90(pred_spectrogram), interpolation="none")
+	fig.colorbar(mappable=im, shrink=0.65, orientation="horizontal", ax=ax2)
+
+	plt.tight_layout()
+	plt.savefig(path, format="png")
+	plt.close()