#
# Copyright (C) 2017 The Android Open Source Project
#
# Licensed under the Apache License, Version 2.0 (the "License");
# you may not use this file except in compliance with the License.
# You may obtain a copy of the License at
#
#      http://www.apache.org/licenses/LICENSE-2.0
#
# Unless required by applicable law or agreed to in writing, software
# distributed under the License is distributed on an "AS IS" BASIS,
# WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
# See the License for the specific language governing permissions and
# limitations under the License.
#

# LSTM Test, With Peephole, With Projection, No Clipping

model = Model()

n_batch = 2
n_input = 5
# n_cell and n_output have the same size when there is no projection.
n_cell = 20
n_output = 16

input = Input("input", "TENSOR_FLOAT32", "{%d, %d}" % (n_batch, n_input))

input_to_input_weights = Input("input_to_input_weights", "TENSOR_FLOAT32", "{%d, %d}" % (n_cell, n_input))
input_to_forget_weights = Input("input_to_forget_weights", "TENSOR_FLOAT32", "{%d, %d}" % (n_cell, n_input))
input_to_cell_weights = Input("input_to_cell_weights", "TENSOR_FLOAT32", "{%d, %d}" % (n_cell, n_input))
input_to_output_weights = Input("input_to_output_weights", "TENSOR_FLOAT32", "{%d, %d}" % (n_cell, n_input))

recurrent_to_input_weights = Input("recurrent_to_intput_weights", "TENSOR_FLOAT32", "{%d, %d}" % (n_cell, n_output))
recurrent_to_forget_weights = Input("recurrent_to_forget_weights", "TENSOR_FLOAT32", "{%d, %d}" % (n_cell, n_output))
recurrent_to_cell_weights = Input("recurrent_to_cell_weights", "TENSOR_FLOAT32", "{%d, %d}" % (n_cell, n_output))
recurrent_to_output_weights = Input("recurrent_to_output_weights", "TENSOR_FLOAT32", "{%d, %d}" % (n_cell, n_output))

cell_to_input_weights = Input("cell_to_input_weights", "TENSOR_FLOAT32", "{%d}" % (n_cell))
cell_to_forget_weights = Input("cell_to_forget_weights", "TENSOR_FLOAT32", "{%d}" %(n_cell))
cell_to_output_weights = Input("cell_to_output_weights", "TENSOR_FLOAT32", "{%d}" % (n_cell))

input_gate_bias = Input("input_gate_bias", "TENSOR_FLOAT32", "{%d}"%(n_cell))
forget_gate_bias = Input("forget_gate_bias", "TENSOR_FLOAT32", "{%d}"%(n_cell))
cell_gate_bias = Input("cell_gate_bias", "TENSOR_FLOAT32", "{%d}"%(n_cell))
output_gate_bias = Input("output_gate_bias", "TENSOR_FLOAT32", "{%d}"%(n_cell))

projection_weights = Input("projection_weights", "TENSOR_FLOAT32", "{%d,%d}" % (n_output, n_cell))
projection_bias = Input("projection_bias", "TENSOR_FLOAT32", "{0}")

output_state_in = Input("output_state_in", "TENSOR_FLOAT32", "{%d, %d}" % (n_batch, n_output))
cell_state_in = Input("cell_state_in", "TENSOR_FLOAT32", "{%d, %d}" % (n_batch, n_cell))

activation_param = Int32Scalar("activation_param", 4)  # Tanh
cell_clip_param = Float32Scalar("cell_clip_param", 0.)
proj_clip_param = Float32Scalar("proj_clip_param", 0.)

scratch_buffer = IgnoredOutput("scratch_buffer", "TENSOR_FLOAT32", "{%d, %d}" % (n_batch, (n_cell * 4)))
output_state_out = IgnoredOutput("output_state_out", "TENSOR_FLOAT32", "{%d, %d}" % (n_batch, n_output))
cell_state_out = IgnoredOutput("cell_state_out", "TENSOR_FLOAT32", "{%d, %d}" % (n_batch, n_cell))
output = Output("output", "TENSOR_FLOAT32", "{%d, %d}" % (n_batch, n_output))

# TODO: need support for more than one output
model = model.Operation("LSTM",
                        input,

                        input_to_input_weights,
                        input_to_forget_weights,
                        input_to_cell_weights,
                        input_to_output_weights,

                        recurrent_to_input_weights,
                        recurrent_to_forget_weights,
                        recurrent_to_cell_weights,
                        recurrent_to_output_weights,

                        cell_to_input_weights,
                        cell_to_forget_weights,
                        cell_to_output_weights,

                        input_gate_bias,
                        forget_gate_bias,
                        cell_gate_bias,
                        output_gate_bias,

                        projection_weights,
                        projection_bias,

                        output_state_in,
                        cell_state_in,

                        activation_param,
                        cell_clip_param,
                        proj_clip_param
).To([scratch_buffer, output_state_out, cell_state_out, output])

input0 = {input_to_input_weights: [
    0.021393683,  0.06124551,    0.046905167,  -0.014657677,  -0.03149463,
    0.09171803,   0.14647801,    0.10797193,   -0.0057968358, 0.0019193048,
    -0.2726754,   0.10154029,    -0.018539885, 0.080349885,   -0.10262385,
    -0.022599787, -0.09121155,   -0.008675967, -0.045206103,  -0.0821282,
    -0.008045952, 0.015478081,   0.055217247,  0.038719587,   0.044153627,
    -0.06453243,  0.05031825,    -0.046935108, -0.008164439,  0.014574226,
    -0.1671009,   -0.15519552,   -0.16819797,  -0.13971269,   -0.11953059,
    0.25005487,   -0.22790983,   0.009855087,  -0.028140958,  -0.11200698,
    0.11295408,   -0.0035217577, 0.054485075,  0.05184695,    0.064711206,
    0.10989193,   0.11674786,    0.03490607,   0.07727357,    0.11390585,
    -0.1863375,   -0.1034451,    -0.13945189,  -0.049401227,  -0.18767063,
    0.042483903,  0.14233552,    0.13832581,   0.18350165,    0.14545603,
    -0.028545704, 0.024939531,   0.050929718,  0.0076203286,  -0.0029723682,
    -0.042484224, -0.11827596,   -0.09171104,  -0.10808628,   -0.16327988,
    -0.2273378,   -0.0993647,    -0.017155107, 0.0023917493,  0.049272764,
    0.0038534778, 0.054764505,   0.089753784,  0.06947234,    0.08014476,
    -0.04544234,  -0.0497073,    -0.07135631,  -0.048929106,  -0.004042012,
    -0.009284026, 0.018042054,   0.0036860977, -0.07427302,   -0.11434604,
    -0.018995456, 0.031487543,   0.012834908,  0.019977754,   0.044256654,
    -0.39292613,  -0.18519334,   -0.11651281,  -0.06809892,   0.011373677],

          input_to_forget_weights: [
              -0.0018401089, -0.004852237,  0.03698424,   0.014181704,   0.028273236,
            -0.016726194,  -0.05249759,   -0.10204261,  0.00861066,    -0.040979505,
            -0.009899187,  0.01923892,    -0.028177269, -0.08535103,   -0.14585495,
            0.10662567,    -0.01909731,   -0.017883534, -0.0047269356, -0.045103323,
            0.0030784295,  0.076784775,   0.07463696,   0.094531395,   0.0814421,
            -0.12257899,   -0.033945758,  -0.031303465, 0.045630626,   0.06843887,
            -0.13492945,   -0.012480007,  -0.0811829,   -0.07224499,   -0.09628791,
            0.045100946,   0.0012300825,  0.013964662,  0.099372394,   0.02543059,
            0.06958324,    0.034257296,   0.0482646,    0.06267997,    0.052625068,
            0.12784666,    0.07077897,    0.025725935,  0.04165009,    0.07241905,
            0.018668644,   -0.037377294,  -0.06277783,  -0.08833636,   -0.040120605,
            -0.011405586,  -0.007808335,  -0.010301386, -0.005102167,  0.027717464,
            0.05483423,    0.11449111,    0.11289652,   0.10939839,    0.13396506,
            -0.08402166,   -0.01901462,   -0.044678304, -0.07720565,   0.014350063,
            -0.11757958,   -0.0652038,    -0.08185733,  -0.076754324,  -0.092614375,
            0.10405491,    0.052960336,   0.035755895,  0.035839386,   -0.012540553,
            0.036881298,   0.02913376,    0.03420159,   0.05448447,    -0.054523353,
            0.02582715,    0.02327355,    -0.011857179, -0.0011980024, -0.034641717,
            -0.026125094,  -0.17582615,   -0.15923657,  -0.27486774,   -0.0006143371,
            0.0001771948,  -8.470171e-05, 0.02651807,   0.045790765,   0.06956496],

          input_to_cell_weights: [
              -0.04580283,   -0.09549462,   -0.032418985,  -0.06454633,
            -0.043528453,  0.043018587,   -0.049152344,  -0.12418144,
            -0.078985475,  -0.07596889,   0.019484362,   -0.11434962,
            -0.0074034138, -0.06314844,   -0.092981495,  0.0062155537,
            -0.025034338,  -0.0028890965, 0.048929527,   0.06235075,
            0.10665918,    -0.032036792,  -0.08505916,   -0.10843358,
            -0.13002433,   -0.036816437,  -0.02130134,   -0.016518239,
            0.0047691227,  -0.0025825808, 0.066017866,   0.029991534,
            -0.10652836,   -0.1037554,    -0.13056071,   -0.03266643,
            -0.033702414,  -0.006473424,  -0.04611692,   0.014419339,
            -0.025174323,  0.0396852,     0.081777506,   0.06157468,
            0.10210095,    -0.009658194,  0.046511717,   0.03603906,
            0.0069369148,  0.015960095,   -0.06507666,   0.09551598,
            0.053568836,   0.06408714,    0.12835667,    -0.008714329,
            -0.20211966,   -0.12093674,   0.029450472,   0.2849013,
            -0.029227901,  0.1164364,     -0.08560263,   0.09941786,
            -0.036999565,  -0.028842626,  -0.0033637602, -0.017012902,
            -0.09720865,   -0.11193351,   -0.029155117,  -0.017936034,
            -0.009768936,  -0.04223324,   -0.036159635,  0.06505112,
            -0.021742892,  -0.023377212,  -0.07221364,   -0.06430552,
            0.05453865,    0.091149814,   0.06387331,    0.007518393,
            0.055960953,   0.069779344,   0.046411168,   0.10509911,
            0.07463894,    0.0075130584,  0.012850982,   0.04555431,
            0.056955688,   0.06555285,    0.050801456,   -0.009862683,
            0.00826772,    -0.026555609,  -0.0073611983, -0.0014897042],

          input_to_output_weights: [
              -0.0998932,   -0.07201956,  -0.052803773,  -0.15629593,  -0.15001918,
            -0.07650751,  0.02359855,   -0.075155355,  -0.08037709,  -0.15093534,
            0.029517552,  -0.04751393,  0.010350531,   -0.02664851,  -0.016839722,
            -0.023121163, 0.0077019283, 0.012851257,   -0.05040649,  -0.0129761,
            -0.021737747, -0.038305793, -0.06870586,   -0.01481247,  -0.001285394,
            0.10124236,   0.083122835,  0.053313006,   -0.062235646, -0.075637154,
            -0.027833903, 0.029774971,  0.1130802,     0.09218906,   0.09506135,
            -0.086665764, -0.037162706, -0.038880914,  -0.035832845, -0.014481564,
            -0.09825003,  -0.12048569,  -0.097665586,  -0.05287633,  -0.0964047,
            -0.11366429,  0.035777505,  0.13568819,    0.052451383,  0.050649304,
            0.05798951,   -0.021852335, -0.099848844,  0.014740475,  -0.078897946,
            0.04974699,   0.014160473,  0.06973932,    0.04964942,   0.033364646,
            0.08190124,   0.025535367,  0.050893165,   0.048514254,  0.06945813,
            -0.078907564, -0.06707616,  -0.11844508,   -0.09986688,  -0.07509403,
            0.06263226,   0.14925587,   0.20188436,    0.12098451,   0.14639415,
            0.0015017595, -0.014267382, -0.03417257,   0.012711468,  0.0028300495,
            -0.024758482, -0.05098548,  -0.0821182,    0.014225672,  0.021544158,
            0.08949725,   0.07505268,   -0.0020780868, 0.04908258,   0.06476295,
            -0.022907063, 0.027562456,  0.040185735,   0.019567577,  -0.015598739,
            -0.049097303, -0.017121866, -0.083368234,  -0.02332002,  -0.0840956],

          input_gate_bias:  [
              0.02234832,  0.14757581,   0.18176508,  0.10380666,  0.053110216,
              -0.06928846, -0.13942584,  -0.11816189, 0.19483899,  0.03652339,
              -0.10250295, 0.036714908,  -0.18426876, 0.036065217, 0.21810818,
              0.02383196,  -0.043370757, 0.08690144,  -0.04444982, 0.00030581196],

          forget_gate_bias: [
              0.035185695, -0.042891346, -0.03032477, 0.23027696,
              0.11098921,  0.15378423,   0.09263801,  0.09790885,
              0.09508917,  0.061199076,  0.07665568,  -0.015443159,
              -0.03499149, 0.046190713,  0.08895977,  0.10899629,
              0.40694186,  0.06030037,   0.012413437, -0.06108739],

          cell_gate_bias:   [
              -0.024379363, 0.0055531194, 0.23377132,   0.033463873,
            -0.1483596,   -0.10639995,  -0.091433935, 0.058573797,
            -0.06809782,  -0.07889636,  -0.043246906, -0.09829136,
            -0.4279842,   0.034901652,  0.18797937,   0.0075234566,
            0.016178843,  0.1749513,    0.13975595,   0.92058027],

          output_gate_bias: [
              0.046159424,  -0.0012809046, 0.03563469,   0.12648113, 0.027195795,
              0.35373217,   -0.018957434,  0.008907322,  -0.0762701, 0.12018895,
              0.04216877,   0.0022856654,  0.040952638,  0.3147856,  0.08225149,
              -0.057416286, -0.14995944,   -0.008040261, 0.13208859, 0.029760877],

          recurrent_to_input_weights: [
              -0.001374326,   -0.078856036,   0.10672688,    0.029162422,
            -0.11585556,    0.02557986,     -0.13446963,   -0.035785314,
            -0.01244275,    0.025961924,    -0.02337298,   -0.044228926,
            -0.055839065,   -0.046598054,   -0.010546039,  -0.06900766,
            0.027239809,    0.022582639,    -0.013296484,  -0.05459212,
            0.08981,        -0.045407712,   0.08682226,    -0.06867011,
            -0.14390695,    -0.02916037,    0.000996957,   0.091420636,
            0.14283475,     -0.07390571,    -0.06402044,   0.062524505,
            -0.093129106,   0.04860203,     -0.08364217,   -0.08119002,
            0.009352075,    0.22920375,     0.0016303885,  0.11583097,
            -0.13732095,    0.012405723,    -0.07551853,   0.06343048,
            0.12162708,     -0.031923793,   -0.014335606,  0.01790974,
            -0.10650317,    -0.0724401,     0.08554849,    -0.05727212,
            0.06556731,     -0.042729504,   -0.043227166,  0.011683251,
            -0.013082158,   -0.029302018,   -0.010899579,  -0.062036745,
            -0.022509435,   -0.00964907,    -0.01567329,   0.04260106,
            -0.07787477,    -0.11576462,    0.017356863,   0.048673786,
            -0.017577527,   -0.05527947,    -0.082487635,  -0.040137455,
            -0.10820036,    -0.04666372,    0.022746278,   -0.07851417,
            0.01068115,     0.032956902,    0.022433773,   0.0026891115,
            0.08944216,     -0.0685835,     0.010513544,   0.07228705,
            0.02032331,     -0.059686817,   -0.0005566496, -0.086984694,
            0.040414046,    -0.1380399,     0.094208956,   -0.05722982,
            0.012092817,    -0.04989123,    -0.086576,     -0.003399834,
            -0.04696032,    -0.045747425,   0.10091314,    0.048676282,
            -0.029037097,   0.031399418,    -0.0040285117, 0.047237843,
            0.09504992,     0.041799378,    -0.049185462,  -0.031518843,
            -0.10516937,    0.026374253,    0.10058866,    -0.0033195973,
            -0.041975245,   0.0073591834,   0.0033782164,  -0.004325073,
            -0.10167381,    0.042500053,    -0.01447153,   0.06464186,
            -0.017142897,   0.03312627,     0.009205989,   0.024138335,
            -0.011337001,   0.035530265,    -0.010912711,  0.0706555,
            -0.005894094,   0.051841937,    -0.1401738,    -0.02351249,
            0.0365468,      0.07590991,     0.08838724,    0.021681072,
            -0.10086113,    0.019608743,    -0.06195883,   0.077335775,
            0.023646897,    -0.095322326,   0.02233014,    0.09756986,
            -0.048691444,   -0.009579111,   0.07595467,    0.11480546,
            -0.09801813,    0.019894179,    0.08502348,    0.004032281,
            0.037211012,    0.068537936,    -0.048005626,  -0.091520436,
            -0.028379958,   -0.01556313,    0.06554592,    -0.045599163,
            -0.01672207,    -0.020169014,   -0.011877351,  -0.20212261,
            0.010889619,    0.0047078193,   0.038385306,   0.08540671,
            -0.017140968,   -0.0035865551,  0.016678626,   0.005633034,
            0.015963363,    0.00871737,     0.060130805,   0.028611384,
            0.10109069,     -0.015060172,   -0.07894427,   0.06401885,
            0.011584063,    -0.024466386,   0.0047652307,  -0.09041358,
            0.030737216,    -0.0046374933,  0.14215417,    -0.11823516,
            0.019899689,    0.006106124,    -0.027092824,  0.0786356,
            0.05052217,     -0.058925,      -0.011402121,  -0.024987547,
            -0.0013661642,  -0.06832946,    -0.015667673,  -0.1083353,
            -0.00096863037, -0.06988685,    -0.053350925,  -0.027275559,
            -0.033664223,   -0.07978348,    -0.025200296,  -0.017207067,
            -0.058403496,   -0.055697463,   0.005798788,   0.12965427,
            -0.062582195,   0.0013350133,   -0.10482091,   0.0379771,
            0.072521195,    -0.0029455067,  -0.13797039,   -0.03628521,
            0.013806405,    -0.017858358,   -0.01008298,   -0.07700066,
            -0.017081132,   0.019358726,    0.0027079724,  0.004635139,
            0.062634714,    -0.02338735,    -0.039547626,  -0.02050681,
            0.03385117,     -0.083611414,   0.002862572,   -0.09421313,
            0.058618143,    -0.08598433,    0.00972939,    0.023867095,
            -0.053934585,   -0.023203006,   0.07452513,    -0.048767887,
            -0.07314807,    -0.056307215,   -0.10433547,   -0.06440842,
            0.04328182,     0.04389765,     -0.020006588,  -0.09076438,
            -0.11652589,    -0.021705797,   0.03345259,    -0.010329105,
            -0.025767034,   0.013057034,    -0.07316461,   -0.10145612,
            0.06358255,     0.18531723,     0.07759293,    0.12006465,
            0.1305557,      0.058638252,    -0.03393652,   0.09622831,
            -0.16253184,    -2.4580743e-06, 0.079869635,   -0.070196845,
            -0.005644518,   0.06857898,     -0.12598175,   -0.035084512,
            0.03156317,     -0.12794146,    -0.031963028,  0.04692781,
            0.030070418,    0.0071660685,   -0.095516115,  -0.004643372,
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              0.03541868,    -0.094149634, -0.034814864, 0.003128424,    -0.020674974,
              -0.03944324,   -0.008110165, -0.11113267,  0.08484226,     0.043586485,
              0.040582247,   0.0968012,    -0.065249965, -0.028036479,   0.0050708856,
              0.0017462453,  0.0326779,    0.041296225,  0.09164146,     -0.047743853,
              -0.015952192,  -0.034451712, 0.084197424,  -0.05347844,    -0.11768019,
              0.085926116,   -0.08251791,  -0.045081906, 0.0948852,      0.068401024,
              0.024856757,   0.06978981,   -0.057309967, -0.012775832,   -0.0032452994,
              0.01977615,    -0.041040014, -0.024264973, 0.063464895,    0.05431621],

          cell_to_input_weights: [
              0.040369894, 0.030746894,  0.24704495,  0.018586371,  -0.037586458,
              -0.15312155, -0.11812848,  -0.11465643, 0.20259799,   0.11418174,
              -0.10116027, -0.011334949, 0.12411352,  -0.076769054, -0.052169047,
              0.21198851,  -0.38871562,  -0.09061183, -0.09683246,  -0.21929175],

          cell_to_forget_weights: [
              -0.01998659,  -0.15568835,  -0.24248174,   -0.012770197, 0.041331276,
            -0.072311886, -0.052123554, -0.0066330447, -0.043891653, 0.036225766,
            -0.047248036, 0.021479502,  0.033189066,   0.11952997,   -0.020432774,
            0.64658105,   -0.06650122,  -0.03467612,   0.095340036,  0.23647355],

          cell_to_output_weights: [
              0.08286371,  -0.08261836, -0.51210177, 0.002913762, 0.17764764,
              -0.5495371,  -0.08460716, -0.24552552, 0.030037103, 0.04123544,
              -0.11940523, 0.007358328, 0.1890978,   0.4833202,   -0.34441817,
              0.36312827,  -0.26375428, 0.1457655,   -0.19724406, 0.15548733],

          projection_weights: [
              -0.009802181,  0.09401916,    0.0717386,     -0.13895074,  0.09641832,
            0.060420845,   0.08539281,    0.054285463,   0.061395317,  0.034448683,
            -0.042991187,  0.019801661,   -0.16840284,   -0.015726732, -0.23041931,
            -0.024478018,  -0.10959692,   -0.013875541,  0.18600968,   -0.061274476,
            0.0138165,     -0.08160894,   -0.07661644,   0.032372914,  0.16169067,
            0.22465782,    -0.03993472,   -0.004017731,  0.08633481,   -0.28869787,
            0.08682067,    0.17240396,    0.014975425,   0.056431185,  0.031037588,
            0.16702051,    0.0077946745,  0.15140012,    0.29405436,   0.120285,
            -0.188994,     -0.027265169,  0.043389652,   -0.022061434, 0.014777949,
            -0.20203483,   0.094781205,   0.19100232,    0.13987629,   -0.036132768,
            -0.06426278,   -0.05108664,   0.13221376,    0.009441198,  -0.16715929,
            0.15859416,    -0.040437475,  0.050779544,   -0.022187516, 0.012166504,
            0.027685808,   -0.07675938,   -0.0055694645, -0.09444123,  0.0046453946,
            0.050794356,   0.10770313,    -0.20790008,   -0.07149004,  -0.11425117,
            0.008225835,   -0.035802525,  0.14374903,    0.15262283,   0.048710253,
            0.1847461,     -0.007487823,  0.11000021,    -0.09542012,  0.22619456,
            -0.029149994,  0.08527916,    0.009043713,   0.0042746216, 0.016261552,
            0.022461696,   0.12689082,    -0.043589946,  -0.12035478,  -0.08361797,
            -0.050666027,  -0.1248618,    -0.1275799,    -0.071875185, 0.07377272,
            0.09944291,    -0.18897448,   -0.1593054,    -0.06526116,  -0.040107165,
            -0.004618631,  -0.067624845,  -0.007576253,  0.10727444,   0.041546922,
            -0.20424393,   0.06907816,    0.050412357,   0.00724631,   0.039827548,
            0.12449835,    0.10747581,    0.13708383,    0.09134148,   -0.12617786,
            -0.06428341,   0.09956831,    0.1208086,     -0.14676677,  -0.0727722,
            0.1126304,     0.010139365,   0.015571211,   -0.038128063, 0.022913318,
            -0.042050496,  0.16842307,    -0.060597885,  0.10531834,   -0.06411776,
            -0.07451711,   -0.03410368,   -0.13393489,   0.06534304,   0.003620307,
            0.04490757,    0.05970546,    0.05197996,    0.02839995,   0.10434969,
            -0.013699693,  -0.028353551,  -0.07260381,   0.047201227,  -0.024575593,
            -0.036445823,  0.07155557,    0.009672501,   -0.02328883,  0.009533515,
            -0.03606021,   -0.07421458,   -0.028082801,  -0.2678904,   -0.13221288,
            0.18419984,    -0.13012612,   -0.014588381,  -0.035059117, -0.04824723,
            0.07830115,    -0.056184657,  0.03277091,    0.025466874,  0.14494097,
            -0.12522776,   -0.098633975,  -0.10766018,   -0.08317623,  0.08594209,
            0.07749552,    0.039474737,   0.1776665,     -0.07409566,  -0.0477268,
            0.29323658,    0.10801441,    0.1154011,     0.013952499,  0.10739139,
            0.10708251,    -0.051456142,  0.0074137426,  -0.10430189,  0.10034707,
            0.045594677,   0.0635285,     -0.0715442,    -0.089667566, -0.10811871,
            0.00026344223, 0.08298446,    -0.009525053,  0.006585689,  -0.24567553,
            -0.09450807,   0.09648481,    0.026996298,   -0.06419476,  -0.04752702,
            -0.11063944,   -0.23441927,   -0.17608605,   -0.052156363, 0.067035615,
            0.19271925,    -0.0032889997, -0.043264326,  0.09663576,   -0.057112187,
            -0.10100678,   0.0628376,     0.04447668,    0.017961001,  -0.10094388,
            -0.10190601,   0.18335468,    0.10494553,    -0.052095775, -0.0026118709,
            0.10539724,    -0.04383912,   -0.042349473,  0.08438151,   -0.1947263,
            0.02251204,    0.11216432,    -0.10307853,   0.17351969,   -0.039091777,
            0.08066188,    -0.00561982,   0.12633002,    0.11335965,   -0.0088127935,
            -0.019777594,  0.06864014,    -0.059751723,  0.016233567,  -0.06894641,
            -0.28651384,   -0.004228674,  0.019708522,   -0.16305895,  -0.07468996,
            -0.0855457,    0.099339016,   -0.07580735,   -0.13775392,  0.08434318,
            0.08330512,    -0.12131499,   0.031935584,   0.09180414,   -0.08876437,
            -0.08049874,   0.008753825,   0.03498998,    0.030215185,  0.03907079,
            0.089751154,   0.029194152,   -0.03337423,   -0.019092513, 0.04331237,
            0.04299654,    -0.036394123,  -0.12915532,   0.09793732,   0.07512415,
            -0.11319543,   -0.032502122,  0.15661901,    0.07671967,   -0.005491124,
            -0.19379048,   -0.218606,     0.21448623,    0.017840758,  0.1416943,
            -0.07051762,   0.19488361,    0.02664691,    -0.18104725,  -0.09334311,
            0.15026465,    -0.15493552,   -0.057762887,  -0.11604192,  -0.262013,
            -0.01391798,   0.012185008,   0.11156489,    -0.07483202,  0.06693364,
            -0.26151478,   0.046425626,   0.036540434,   -0.16435726,  0.17338543,
            -0.21401681,   -0.11385144,   -0.08283257,   -0.069031075, 0.030635102,
            0.010969227,   0.11109743,    0.010919218,   0.027526086,  0.13519906,
            0.01891392,    -0.046839405,  -0.040167913,  0.017953383,  -0.09700955,
            0.0061885654,  -0.07000971,   0.026893595,   -0.038844477, 0.14543656],

          projection_bias: [],
}

# Batch0: 4 (input_sequence_size) * 5 (n_input)
input0[input] = [0.867394, 0.291279, 0.013714, 0.482521, 0.626339]
# Batch1: 4 (input_sequence_size) * 5 (n_input)
input0[input].extend(
    [0.082922, 0.563329, 0.865614, 0.333232, 0.259916]
)
input0[output_state_in] = [
    -0.0213783, 0.0350169, 0.000324787, 0.0276012,
    -0.0263374, -0.0371449, 0.0446149, -0.0205474,
    0.0103729, -0.0576349, -0.0150052, -0.0292043,
    0.0376827, 0.0136115, 0.0243435, 0.0354492,
    -0.0204549, 0.0450315, -0.00117379, 0.0167673,
    -0.0375007, -0.0238314, 0.038784, -0.0174034,
    0.0131743, -0.0506589, -0.00484469, -0.0240239,
    0.0325789, 0.00790064, 0.0220157, 0.0333314,
]
input0[cell_state_in] = [
    -0.126572, -0.121882, 0.121569, 0.0489971,
    -0.240177, -0.124685, -0.122565, 0.0162748,
    0.0317536, -0.0270355, 0.0418199, -0.179755,
    -0.327279, -0.0342741, 0.133831, -0.0238279,
    0.122148, 0.269115, 0.185989, 0.525976,
    -0.167208, -0.109612, 0.0531226, 0.0695387,
    -0.248335, -0.134123, -0.108246, 0.00628498,
    0.0492984, -0.0264919, 0.0698144, -0.0635602,
    -0.295363, -0.0760078, 0.102725, -0.0351708,
    0.149804, 0.259131, 0.202573, 0.500664,
]
output0 = {
  scratch_buffer: [ 0 for x in range(n_batch * n_cell * 4) ],
  cell_state_out: [ 0 for x in range(n_batch * n_cell) ],
  output_state_out: [ 0 for x in range(n_batch * n_output) ],
}

# Batch0: 4 (input_sequence_size) * 16 (n_output)
output0[output] = [
    -0.0189322,  0.0464512, -0.00251373, 0.0225745,
    -0.0308346,  -0.0317124,  0.0460407, -0.0189395,
    0.0149363,    -0.0530162,  -0.0150767,  -0.0340193,
    0.0286833,   0.00824207,   0.0264887,   0.0305169]
# Batch1: 4 (input_sequence_size) * 16 (n_output)
output0[output].extend(
    [-0.0264787,  0.0387855, -0.000764675, 0.0217599,
     -0.037537,   -0.0335206,  0.0431679, -0.0211424,
     0.010203,    -0.062785,   -0.00832363, -0.025181,
     0.0412031,    0.0118723,   0.0239643,   0.0394009]
    )

Example((input0, output0))
