class_docstr: Testing conversion of BatchMatMul in TF-TRT conversion.
class_docstr_tok: ["Testing","conversion","of","BatchMatMul","in","TF-TRT","conversion","."]
code: def GraphFn(self, inp):
      dtype = inp.dtype
      e1 = constant_op.constant(
          np.random.randn(1, 1, 3, 5), name="kernel_1", dtype=dtype
      )
      e2 = constant_op.constant(
          np.random.randn(1, 1, 5, 10), name="kernel_2", dtype=dtype
      )
      conv = nn.conv2d(
          input=inp,
          filter=e1,
          strides=[1, 1, 1, 1],
          padding="VALID",
          name="conv",
      )
      out = nn.conv2d(
          input=conv,
          filter=e2,
          strides=[1, 1, 1, 1],
          padding="VALID",
          name="conv_2",
      )
      return array_ops.squeeze(out, name="output_0")
  
file_path: tensorflow/tensorflow/python/compiler/tensorrt/test/memory_alignment_test.py
imports: import numpy
  from tensorflow.python.compiler.tensorrt.test import tf_trt_integration_test_base
  from tensorflow.python.framework import constant_op
  from tensorflow.python.framework import dtypes
  from tensorflow.python.framework import test_util
  from tensorflow.python.ops import array_ops
  from tensorflow.python.ops import nn
  from tensorflow.python.platform import test
label_desc: Use image node_id 1 for calling the MemoryAlignmentTest obj's underlying member method code with example usage: obj.GraphFn(inp) and returns: array_ops