class_docstr: Quantization tests for dynamic Int8 - Int8 matrix multiplications
class_docstr_tok: ["Quantization","tests","for","dynamic","Int8","-","Int8","matrix","multiplications"]
code: def test_batched_matmul_min_input_channels_invalid(self):
      self.initialize()
      self.builder.add_batched_mat_mul(
          name="batched_matmul",
          input_names=["data"],
          output_name="output",
          weight_matrix_rows=self.Cin,
          weight_matrix_columns=self.Cout,
          W=self.W,
      )
      self.selector.minimum_input_channels = 33
      self.compare(specification_modified=False)
  
imports: import itertools
  import unittest
  import numpy
  import pytest
  import coremltools
  import coremltools.models.datatypes
  from coremltools import ComputeUnit
  from coremltools.models import _QUANTIZATION_MODE_LINEAR_QUANTIZATION, neural_network
  from coremltools.models.neural_network import quantization_utils
  from coremltools.models.neural_network.quantization_utils import MatrixMultiplyLayerSelector, _quantize_spec_weights, activate_int8_int8_matrix_multiplications
label_desc: Use image node_id 11 for calling the DynamicQuantizedInt8Int8MatMul obj's underlying member method code with example usage: obj.test_batched_matmul_min_input_channels_invalid() without return types