a Sic!@sLdZddlZddlmZGdddejZeZGdddejZeZ dS)zCTensorBoard encoder helper module. Encoder depends on TensorFlow. N) op_evaluatorcs0eZdZdZfddZddZddZZS)_TensorFlowPngEncoderabEncode an image to PNG. This function is thread-safe, and has high performance when run in parallel. See `encode_png_benchmark.py` for details. Arguments: image: A numpy array of shape `[height, width, channels]`, where `channels` is 1, 3, or 4, and of dtype uint8. Returns: A bytestring with PNG-encoded data. cstt|d|_d|_dSN)superr__init___image_placeholder _encode_opself __class__T/var/www/html/django/DPS/env/lib/python3.9/site-packages/tensorboard/util/encoder.pyr(sz_TensorFlowPngEncoder.__init__cCs8ddlmm}|j|jdd|_|j|j|_dS)Nrimage_to_encodedtypename) tensorflow.compat.v1compatv1 placeholderuint8rimage encode_pngrr tfr r rinitialize_graph-s z&_TensorFlowPngEncoder.initialize_graphcCsFt|tjstd||jtjkr2td|j|jj|j|idS)Nz!'image' must be a numpy array: %rz&'image' dtype must be uint8, but is %r feed_dict) isinstancenpndarray ValueErrorrrrevalr)r rr r rrun6s   z_TensorFlowPngEncoder.run__name__ __module__ __qualname____doc__rrr$ __classcell__r r r rrs  rcs0eZdZdZfddZddZddZZS)_TensorFlowWavEncodera!Encode an audio clip to WAV. This function is thread-safe and exhibits good parallel performance. Arguments: audio: A numpy array of shape `[samples, channels]`. samples_per_second: A positive `int`, in Hz. Returns: A bytestring with WAV-encoded data. cs$tt|d|_d|_d|_dSr)rr+r_audio_placeholder_samples_per_second_placeholderrr r r rrPsz_TensorFlowWavEncoder.__init__cCsPddlmm}|j|jdd|_|j|jdd|_|jj |j|jd|_ dS)Nrrrsamples_per_second) sample_rate) rrrrfloat32r,int32r-audio encode_wavrrr r rrVsz&_TensorFlowWavEncoder.initialize_graphcCsLt|tjstd|t|ts.td||j||j|i}|jj|dS)Nz!'audio' must be a numpy array: %rz''samples_per_second' must be an int: %rr) rr r!r"intr,r-rr#)r r2r.rr r rr$es   z_TensorFlowWavEncoder.runr%r r r rr+Cs r+) r)numpyr tensorboard.utilrZPersistentOpEvaluatorrrr+r3r r r rs  &2