<glob pattern="*.pptm"/>
    <sub-class-of type="application/x-tika-ooxml"/>
  </mime-type>

  <mime-type type="application/vnd.ms-powerpoint.slide.macroenabled.12">
    <glob pattern="*.sldm"/>
    <sub-class-of type="application/x-tika-ooxml"/>
  </mime-type>

  <mime-type type="application/vnd.ms-powerpoint.slideshow.macroenabled.12">

	MOVW $2147483648, R5            // 64058000
	MOVWZ $-2147483648, R5          // 3ca08000

	// TODO: These are preprocessed by the assembler into MOVD $const>>shift, R5; SLD $shift, R5.
	//       This only captures the MOVD. Should the SLD be appended to the encoding by the test?
	// Hex constant 0x20004000000
	MOVD $2199090364416, R5         // 60058001
	// Hex constant 0xFFFFFE0004000000

	SRW	$4, R4, R7              // eb74000400de
	SRW	R1, R4, R7              // eb74100000de
	SLW	$4, R3, R6              // eb63000400df
	SLW	R2, R3, R6              // eb63200000df
	SLD	$4, R3, R6              // eb630004000d
	SLD	R2, R3, R6              // eb632000000d
	SRAD	$4, R5, R8              // eb850004000a
	SRAD	R3, R5, R8              // eb853000000a
	SRAW	$4, R5, R8              // eb85000400dc

        "//third_party/cloud_tpu/inference_converter/...",
        "//third_party/py/cloud_ml_autoflow/...",
        "//third_party/py/envlogger/...",
        "//third_party/py/gldm/...",
        "//third_party/py/guesslang/...",
        "//third_party/py/keras/...",
        "//third_party/py/tf_keras/...",
        "//third_party/yggdrasil_decision_forests/...",

R7=len // setup parameters MOVD cnt+112(FP), R8 XC $12, (R1), (R1) // reserved MVC $4, 12(R8), 12(R1) // set chain value MVC $16, (R8), 64(R1) // set initial counter value XC $32, 16(R1), 16(R1) // set hash subkey and tag SLD $3, R7, R12 MOVD R12, 48(R1) // set total AAD length SLD $3, R5, R12 MOVD R12, 56(R1) // set total plaintext/ciphertext length LMG key+8(FP), R8, R9 // R8=base R9=len MVC $16, (R8), 80(R1) // set key CMPBEQ R9, $16, kma MVC $8, 16(R8), 96(R1) CMPBEQ R9, $24, kma MVC $8, 24(R8),...

*   Added graph-construction C API
*   Major revision to the graph-construction C++ API
*   Support makefile build for iOS
*   Added Mac GPU support
*   Full version of TF-Slim available as `tf.contrib.slim`
*   Added k-Means clustering and WALS matrix factorization

## Bug Fixes and Other Changes

*   Allow gradient computation for scalar values.
*   Performance improvements for gRPC