class_docstr: Operator converter for Conv.
class_docstr_tok: ["Operator","converter","for","Conv","."]
code: def _impl(cls, inputs, args, params):
      # get number of channels
      channels = infer_channels(inputs[1])
      args["channels"] = channels
      _clean_up_pool_args(args)
      out = AttrCvt(
          op_name=dimension_picker("conv"),
          transforms={
              "group": ("groups", 1),
              "kernel_shape": "kernel_size",
              "pads": ("padding", (0, 0), revert_caffe2_pad),
              "strides": "strides",
              "dilations": ("dilation", (1, 1)),
              "order": (
                  "data_layout",
                  ("NCHW"),
                  lambda x: x
                  if isinstance(x, str)
                  else x.decode("UTF-8"),
              ),
          },
          excludes=[],
          ignores=_caffe2_internal_args,
          custom_check=dimension_constraint(),
      )(inputs[:2], args, params)
      use_bias = len(inputs) == 3
      if use_bias:
          out = _op.nn.bias_add(out, inputs[2])
      return out
  
imports: import tvm
  from tvm.ir import IRModule
  from ..None import analysis
  from ..None import expr
  from ..None import function
  from ..None import op
  from ...None import nd
  from .common import AttrCvt, Renamer
  from .common import get_relay_op, new_var, infer_channels
label_desc: Use image node_id 1 for calling the Conv obj's underlying member method code with example usage: obj._impl(cls, inputs, args, params) and returns: out