--lockfile=requirements.txt:./requirements_lock_3_12.txt
        --lockfile=requirements.txt:./ci/official/containers/linux_arm64/devel.requirements.txt
        --lockfile=requirements.txt:./ci/official/containers/linux_arm64/jax.requirements.txt

		instructions[s] = obj.As(i)
	}
	for i, s := range mips.Anames {
		if obj.As(i) >= obj.A_ARCHSPECIFIC {
			instructions[s] = obj.As(i) + obj.ABaseMIPS
		}
	}
	// Annoying alias.
	instructions["JAL"] = mips.AJAL

	return &Arch{
		LinkArch:       linkArch,
		Instructions:   instructions,
		Register:       register,
		RegisterPrefix: registerPrefix,
		RegisterNumber: mipsRegisterNumber,
		IsJump:         jumpMIPS,

    #   h5py
    #   jax
    #   keras-nightly
    #   ml-dtypes
    #   opt-einsum
    #   scipy
    #   tb-nightly
opt-einsum==3.3.0 \
    --hash=sha256:2455e59e3947d3c275477df7f5205b30635e266fe6dc300e3d9f9646bfcea147 \
    --hash=sha256:59f6475f77bbc37dcf7cd748519c0ec60722e91e63ca114e68821c0c54a46549
    # via
    #   -r requirements.in
    #   jax
packaging==23.2 \

        "//tensorflow/compiler/mlir/lite/python:flatbuffer_to_mlir",
        "//tensorflow/compiler/mlir/lite/python:graphdef_to_tfl_flatbuffer",
        "//tensorflow/compiler/mlir/lite/python:jax_to_tfl_flatbuffer",
        "//tensorflow/compiler/mlir/lite/python:saved_model_to_tfl_flatbuffer",
        "//tensorflow/compiler/mlir/lite/quantization/lite:quantize_model",

        tf.constant(2, dtype=tf.int32) b = tf.constant(3, dtype=tf.int32)
        result = client.multiply(a, b)`

*   `tf.lite`:

    *   Add experimental API `experimental_from_jax` to support conversion from
        Jax models to TensorFlow Lite.
    *   Support uint32 data type for cast op.
    *   Support int8 data type for cast op.
    *   Add experimental quantization debugger `tf.lite.QuantizationDebugger`

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