the layer's dtype. If you had a model that used `float64`, it will
        probably silently use `float32` in TensorFlow2, and a warning will be
        issued that starts with Layer "layer-name" is casting an input tensor
        from dtype float64 to the layer's dtype of float32. To fix, either set
        the default dtype to float64 with

mdurl==0.1.2 \
    --hash=sha256:84008a41e51615a49fc9966191ff91509e3c40b939176e643fd50a5c2196b8f8 \
    --hash=sha256:bb413d29f5eea38f31dd4754dd7377d4465116fb207585f97bf925588687c1ba
    # via markdown-it-py
ml-dtypes==0.5.1 \
    --hash=sha256:023ce2f502efd4d6c1e0472cc58ce3640d051d40e71e27386bed33901e201327 \
    --hash=sha256:05f23447a1c20ddf4dc7c2c661aa9ed93fcb2658f1017c204d1e758714dc28a8 \

mdurl==0.1.2 \
    --hash=sha256:84008a41e51615a49fc9966191ff91509e3c40b939176e643fd50a5c2196b8f8 \
    --hash=sha256:bb413d29f5eea38f31dd4754dd7377d4465116fb207585f97bf925588687c1ba
    # via markdown-it-py
ml-dtypes==0.5.1 \
    --hash=sha256:023ce2f502efd4d6c1e0472cc58ce3640d051d40e71e27386bed33901e201327 \
    --hash=sha256:05f23447a1c20ddf4dc7c2c661aa9ed93fcb2658f1017c204d1e758714dc28a8 \

mdurl==0.1.2 \
    --hash=sha256:84008a41e51615a49fc9966191ff91509e3c40b939176e643fd50a5c2196b8f8 \
    --hash=sha256:bb413d29f5eea38f31dd4754dd7377d4465116fb207585f97bf925588687c1ba
    # via markdown-it-py
ml-dtypes==0.5.4 \
    --hash=sha256:0d2ffd05a2575b1519dc928c0b93c06339eb67173ff53acb00724502cda231cf \
    --hash=sha256:11942cbf2cf92157db91e5022633c0d9474d4dfd813a909383bd23ce828a4b7d \

mdurl==0.1.2 \
    --hash=sha256:84008a41e51615a49fc9966191ff91509e3c40b939176e643fd50a5c2196b8f8 \
    --hash=sha256:bb413d29f5eea38f31dd4754dd7377d4465116fb207585f97bf925588687c1ba
    # via markdown-it-py
ml-dtypes==0.5.1 \
    --hash=sha256:023ce2f502efd4d6c1e0472cc58ce3640d051d40e71e27386bed33901e201327 \
    --hash=sha256:05f23447a1c20ddf4dc7c2c661aa9ed93fcb2658f1017c204d1e758714dc28a8 \

mdurl==0.1.2 \
    --hash=sha256:84008a41e51615a49fc9966191ff91509e3c40b939176e643fd50a5c2196b8f8 \
    --hash=sha256:bb413d29f5eea38f31dd4754dd7377d4465116fb207585f97bf925588687c1ba
    # via markdown-it-py
ml-dtypes==0.5.4 \
    --hash=sha256:0d2ffd05a2575b1519dc928c0b93c06339eb67173ff53acb00724502cda231cf \
    --hash=sha256:11942cbf2cf92157db91e5022633c0d9474d4dfd813a909383bd23ce828a4b7d \

		riscv.AAMOMINW, riscv.AAMOMIND, riscv.AAMOMINUW, riscv.AAMOMINUD,
		riscv.AAMOMAXW, riscv.AAMOMAXD, riscv.AAMOMAXUW, riscv.AAMOMAXUD:
		return true
	}
	return false
}

// IsRISCV64VTypeI reports whether op is a vtype immediate instruction that
// requires special handling.
func IsRISCV64VTypeI(op obj.As) bool {
	return op == riscv.AVSETVLI || op == riscv.AVSETIVLI
}

// IsRISCV64CSRO reports whether the op is an instruction that uses

{
  "properties": {
    "hostname": {
      "type": "keyword"
    },
    "level": {
      "type": "keyword"
    },
    "loggerName": {
      "type": "keyword"
    },
    "message": {
      "type": "text",
      "index": false
    },
    "throwable": {
      "type": "text",
      "index": false
    },
    "timestamp": {
      "type": "date",
      "format": "epoch_millis"
    }
  }

to those values. A type may be denoted by a <i>type name</i>, if it has one, which must be
followed by <a href="#Instantiations">type arguments</a> if the type is generic.
A type may also be specified using a <i>type literal</i>, which composes a type
from existing types.
</p>

<pre class="ebnf">
Type     = TypeName [ TypeArgs ] | TypeLit | "(" Type ")" .
TypeName = identifier | QualifiedIdent .

    return this;
  }

  /**
   * Sets distinct values for {@code type}, so that when a class {@code Foo} is tested for {@link
   * Object#equals} and {@link Object#hashCode}, and its construction requires a parameter of {@code
   * type}, the distinct values of {@code type} can be passed as parameters to create {@code Foo}
   * instances that are unequal.
   *