{"record":{"id":"efdcf8f404cac2ae","repo":"tensorflow/models","slug":"set-quantize-weights-called-on-layer-with","errorCode":null,"errorMessage":"`set_quantize_weights` called on layer {} with {} weight parameters, but layer expects {} values.","messagePattern":"`set_quantize_weights` called on layer (.+?) with (.+?) weight parameters, but layer expects (.+?) values\\.","errorType":"exception","errorClass":"ValueError","httpStatus":null,"severity":"error","filePath":"official/projects/qat/nlp/quantization/configs.py","lineNumber":334,"sourceCode":"\n    # TODO(pulkitb): For some layers such as Conv2D, per_axis should be True.\n    # Add mapping for which layers support per_axis.\n    self.weight_quantizer = LastValueQuantizer(\n        num_bits=8, per_axis=False, symmetric=True, narrow_range=True)\n    self.activation_quantizer = MovingAverageQuantizer(\n        num_bits=8, per_axis=False, symmetric=False, narrow_range=False)\n\n  def get_weights_and_quantizers(self, layer):\n    return [(getattr(layer, weight_attr), self.weight_quantizer)\n            for weight_attr in self.weight_attrs]\n\n  def get_activations_and_quantizers(self, layer):\n    return [(getattr(layer, activation_attr), self.activation_quantizer)\n            for activation_attr in self.activation_attrs]\n\n  def set_quantize_weights(self, layer, quantize_weights):\n    if len(self.weight_attrs) != len(quantize_weights):\n      raise ValueError(\n          '`set_quantize_weights` called on layer {} with {} '\n          'weight parameters, but layer expects {} values.'.format(\n              layer.name, len(quantize_weights), len(self.weight_attrs)))\n\n    for weight_attr, weight in zip(self.weight_attrs, quantize_weights):\n      current_weight = getattr(layer, weight_attr)\n      if current_weight.shape != weight.shape:\n        raise ValueError('Existing layer weight shape {} is incompatible with'\n                         'provided weight shape {}'.format(\n                             current_weight.shape, weight.shape))\n\n      setattr(layer, weight_attr, weight)\n\n  def set_quantize_activations(self, layer, quantize_activations):\n    if len(self.activation_attrs) != len(quantize_activations):\n      raise ValueError(\n          '`set_quantize_activations` called on layer {} with {} '\n          'activation parameters, but layer expects {} values.'.format(","sourceCodeStart":316,"sourceCodeEnd":352,"githubUrl":"https://github.com/tensorflow/models/blob/e006f5f0d534913e49c1f1dae87364039fa607e2/official/projects/qat/nlp/quantization/configs.py#L316-L352","documentation":"Error \"`set_quantize_weights` called on layer {} with {} weight parameters, but layer expects {} values.\" thrown in tensorflow/models.","triggerScenarios":"Thrown at official/projects/qat/nlp/quantization/configs.py:334 when the library encounters an invalid state.","commonSituations":"See trigger scenarios.","solutions":[],"exampleFix":null,"handlingStrategy":null,"validationCode":null,"typeGuard":null,"tryCatchPattern":null,"preventionTips":[],"tags":[],"backgroundTag":null,"analyzedSha":"e006f5f0d534913e49c1f1dae87364039fa607e2","analyzedAt":"2026-08-24T14:09:15.576Z","schemaVersion":2},"datasetVersion":"2026-08-24T17:17:21.512Z"}