7 matches found
TensorFlow has Null Pointer Error in QuantizedMatMulWithBiasAndDequantize
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BIT-TENSORFLOW-2023-25670 TensorFlow has Null Pointer Error in QuantizedMatMulWithBiasAndDequantize
TensorFlow is an open source platform for machine learning. Versions prior to 2.12.0 and 2.11.1 have a null point error in QuantizedMatMulWithBiasAndDequantize with MKL enabled. A fix is included in TensorFlow version 2.12.0 and version 2.11.1...
Security Bulletin: IBM Watson Speech Services Cartridge for IBM Cloud Pak for Data is vulnerable to a denial of service in TensorFlow (CVE-2023-25670)
Summary IBM Watson Speech Services Cartridge for IBM Cloud Pak for Data is vulnerable to a denial of service in TensorFlow, caused by a NULL pointer dereference in QuantizedMatMulWithBiasAndDequantize when MKL is enabled CVE-2023-25670. TensorFlow is included as part of the runtimes in our servic...
Stack overflow
TensorFlow is an open source platform for machine learning. Versions prior to 2.12.0 and 2.11.1 have a null point error in QuantizedMatMulWithBiasAndDequantize with MKL enabled. A fix is included in TensorFlow version 2.12.0 and version 2.11.1...
CVE-2023-25670 TensorFlow has Null Pointer Error in QuantizedMatMulWithBiasAndDequantize
TensorFlow is an open source platform for machine learning. Versions prior to 2.12.0 and 2.11.1 have a null point error in QuantizedMatMulWithBiasAndDequantize with MKL enabled. A fix is included in TensorFlow version 2.12.0 and version 2.11.1...
CVE-2023-25670 TensorFlow has Null Pointer Error in QuantizedMatMulWithBiasAndDequantize
TensorFlow is an open source platform for machine learning. Versions prior to 2.12.0 and 2.11.1 have a null point error in QuantizedMatMulWithBiasAndDequantize with MKL enabled. A fix is included in TensorFlow version 2.12.0 and version 2.11.1...
TensorFlow has Null Pointer Error in QuantizedMatMulWithBiasAndDequantize
Impact NPE in QuantizedMatMulWithBiasAndDequantize with MKL enable python import tensorflow as tf func = tf.rawops.QuantizedMatMulWithBiasAndDequantize para='a': tf.constant138, dtype=tf.quint8, 'b': tf.constant4, dtype=tf.qint8, 'bias': 31.81644630432129, 47.21876525878906, 109.95201110839844,...