if tables := strings.Split(stmt.Schema.Table, "."); len(tables) == 2 {
			stmt.TableExpr = &clause.Expr{SQL: stmt.Quote(stmt.Schema.Table)}
			stmt.Table = tables[1]
			return
		}

		stmt.Table = stmt.Schema.Table
	}
	return err
}

func (stmt *Statement) clone() *Statement {
	newStmt := &Statement{

nvidia-cublas-cu12>=12.5.3.2,<13.0
nvidia-cuda-cupti-cu12>=12.5.82,<13.0
nvidia-cuda-nvcc-cu12>=12.5.82,<13.0
nvidia-cuda-nvrtc-cu12>=12.5.82,<13.0
nvidia-cuda-runtime-cu12>=12.5.82,<13.0
# The upper bound is set for the CUDNN API compatibility.
# See
# https://docs.nvidia.com/deeplearning/cudnn/backend/latest/developer/forward-compatibility.html#cudnn-api-compatibility
nvidia-cudnn-cu12>=9.3.0.75,<10.0
nvidia-cufft-cu12>=11.2.3.61,<12.0

    # via
    #   -r ci/official/requirements_updater/requirements.in
    #   h5py
    #   jax
    #   keras-nightly
    #   ml-dtypes
    #   opt-einsum
    #   scipy
    #   tb-nightly
nvidia-cublas-cu12==12.5.3.2 \
    --hash=sha256:4960f3dc5f39699acadf76fa6d94b10a2a00f2956c2c442efa299fb22b0748f3 \
    --hash=sha256:7d0191251180de606023d396b94d66f66470a0ae96d1dbb906c7656ea0f71eda \

    # via
    #   -r ci/official/requirements_updater/requirements.in
    #   h5py
    #   jax
    #   keras-nightly
    #   ml-dtypes
    #   opt-einsum
    #   scipy
    #   tb-nightly
nvidia-cublas-cu12==12.5.3.2 \
    --hash=sha256:4960f3dc5f39699acadf76fa6d94b10a2a00f2956c2c442efa299fb22b0748f3 \
    --hash=sha256:7d0191251180de606023d396b94d66f66470a0ae96d1dbb906c7656ea0f71eda \

    # via
    #   -r ci/official/requirements_updater/requirements.in
    #   h5py
    #   jax
    #   keras-nightly
    #   ml-dtypes
    #   opt-einsum
    #   scipy
    #   tb-nightly
nvidia-cublas-cu12==12.5.3.2 \
    --hash=sha256:4960f3dc5f39699acadf76fa6d94b10a2a00f2956c2c442efa299fb22b0748f3 \
    --hash=sha256:7d0191251180de606023d396b94d66f66470a0ae96d1dbb906c7656ea0f71eda \

    # via
    #   -r ci/official/requirements_updater/requirements.in
    #   h5py
    #   jax
    #   keras-nightly
    #   ml-dtypes
    #   opt-einsum
    #   scipy
    #   tb-nightly
nvidia-cublas-cu12==12.5.3.2 \
    --hash=sha256:4960f3dc5f39699acadf76fa6d94b10a2a00f2956c2c442efa299fb22b0748f3 \
    --hash=sha256:7d0191251180de606023d396b94d66f66470a0ae96d1dbb906c7656ea0f71eda \

    # via
    #   -r ci/official/requirements_updater/requirements.in
    #   h5py
    #   jax
    #   keras-nightly
    #   ml-dtypes
    #   opt-einsum
    #   scipy
    #   tb-nightly
nvidia-cublas-cu12==12.5.3.2 \
    --hash=sha256:4960f3dc5f39699acadf76fa6d94b10a2a00f2956c2c442efa299fb22b0748f3 \
    --hash=sha256:7d0191251180de606023d396b94d66f66470a0ae96d1dbb906c7656ea0f71eda \

    # via
    #   -r ci/official/requirements_updater/requirements.in
    #   h5py
    #   jax
    #   keras-nightly
    #   ml-dtypes
    #   opt-einsum
    #   scipy
    #   tb-nightly
nvidia-cublas-cu12==12.5.3.2 \
    --hash=sha256:4960f3dc5f39699acadf76fa6d94b10a2a00f2956c2c442efa299fb22b0748f3 \
    --hash=sha256:7d0191251180de606023d396b94d66f66470a0ae96d1dbb906c7656ea0f71eda \

    # via
    #   -r ci/official/requirements_updater/requirements.in
    #   h5py
    #   jax
    #   keras-nightly
    #   ml-dtypes
    #   opt-einsum
    #   scipy
    #   tb-nightly
nvidia-cublas-cu12==12.5.3.2 \
    --hash=sha256:4960f3dc5f39699acadf76fa6d94b10a2a00f2956c2c442efa299fb22b0748f3 \
    --hash=sha256:7d0191251180de606023d396b94d66f66470a0ae96d1dbb906c7656ea0f71eda \

    # via
    #   -r ci/official/requirements_updater/requirements.in
    #   h5py
    #   jax
    #   keras-nightly
    #   ml-dtypes
    #   opt-einsum
    #   scipy
    #   tb-nightly
nvidia-cublas-cu12==12.5.3.2 \
    --hash=sha256:4960f3dc5f39699acadf76fa6d94b10a2a00f2956c2c442efa299fb22b0748f3 \
    --hash=sha256:7d0191251180de606023d396b94d66f66470a0ae96d1dbb906c7656ea0f71eda \