/-- The Banach open mapping theorem: if a bounded linear map between Banach spaces is onto, then
any point has a preimage with controlled norm. -/
theorem exists_preimage_norm_le (surj : Surjective f) :
    ∃ C > 0, ∀ y, ∃ x, f x = y ∧ ‖x‖ ≤ C * ‖y‖ := by
  obtain ⟨C, C0, hC⟩ := exists_approx_preimage_norm_le f surj
  /- Second step of the proof: starting from `y`, we want an exact preimage of `y`. Let `g y` be
    the approximate preimage of `y` given by the first step, and `h y = y - f(g y)` the part that
    has no preimage yet. We will iterate this process, taking the approximate preimage of `h y`,
    leaving only `h^2 y` without preimage yet, and so on. Let `u n` be the approximate preimage
    of `h^n y`. Then `u` is a converging series, and by design the sum of the series is a
    preimage of `y`. This uses completeness of `E`. -/
  choose g hg using hC
  let h y := y - f (g y)
  have hle : ∀ y, ‖h y‖ ≤ 1 / 2 * ‖y‖ := by
    intro y
    rw [← dist_eq_norm, dist_comm]
    exact (hg y).1
  refine' ⟨2 * C + 1, by linarith, fun y => _⟩
  have hnle : ∀ n : ℕ, ‖h^[n] y‖ ≤ (1 / 2) ^ n * ‖y‖ := by
    intro n
    induction' n with n IH
    · simp only [one_div, Nat.zero_eq, one_mul, iterate_zero_apply, pow_zero, le_rfl]
    · rw [iterate_succ']
      apply le_trans (hle _) _
      rw [pow_succ, mul_assoc]
      apply mul_le_mul_of_nonneg_left IH
      norm_num
  let u n := g (h^[n] y)
  have ule : ∀ n, ‖u n‖ ≤ (1 / 2) ^ n * (C * ‖y‖) := by
    intro n
    apply le_trans (hg _).2 _
    calc
      C * ‖h^[n] y‖ ≤ C * ((1 / 2) ^ n * ‖y‖) := mul_le_mul_of_nonneg_left (hnle n) C0
      _ = (1 / 2) ^ n * (C * ‖y‖) := by ring
  have sNu : Summable fun n => ‖u n‖ := by
    refine' .of_nonneg_of_le (fun n => norm_nonneg _) ule _
    exact Summable.mul_right _ (summable_geometric_of_lt_1 (by norm_num) (by norm_num))
  have su : Summable u := sNu.of_norm
  let x := tsum u
  have x_ineq : ‖x‖ ≤ (2 * C + 1) * ‖y‖ :=
    calc
      ‖x‖ ≤ ∑' n, ‖u n‖ := norm_tsum_le_tsum_norm sNu
      _ ≤ ∑' n, (1 / 2) ^ n * (C * ‖y‖) :=
        tsum_le_tsum ule sNu (Summable.mul_right _ summable_geometric_two)
      _ = (∑' n, (1 / 2) ^ n) * (C * ‖y‖) := tsum_mul_right
      _ = 2 * C * ‖y‖ := by rw [tsum_geometric_two, mul_assoc]
      _ ≤ 2 * C * ‖y‖ + ‖y‖ := (le_add_of_nonneg_right (norm_nonneg y))
      _ = (2 * C + 1) * ‖y‖ := by ring
  have fsumeq : ∀ n : ℕ, f (∑ i in Finset.range n, u i) = y - h^[n] y := by
    intro n
    induction' n with n IH
    · simp [f.map_zero]
    · rw [sum_range_succ, f.map_add, IH, iterate_succ_apply', sub_add]
  have : Tendsto (fun n => ∑ i in Finset.range n, u i) atTop (𝓝 x) := su.hasSum.tendsto_sum_nat
  have L₁ : Tendsto (fun n => f (∑ i in Finset.range n, u i)) atTop (𝓝 (f x)) :=
    (f.continuous.tendsto _).comp this
  simp only [fsumeq] at L₁
  have L₂ : Tendsto (fun n => y - h^[n] y) atTop (𝓝 (y - 0)) := by
    refine' tendsto_const_nhds.sub _
    rw [tendsto_iff_norm_sub_tendsto_zero]
    simp only [sub_zero]
    refine' squeeze_zero (fun _ => norm_nonneg _) hnle _
    rw [← zero_mul ‖y‖]
    refine' (_root_.tendsto_pow_atTop_nhds_0_of_lt_1 _ _).mul tendsto_const_nhds <;> 

Proof state:
case refine'_2
𝕜 : Type u_1
inst✝⁶ : NontriviallyNormedField 𝕜
E : Type u_2
inst✝⁵ : NormedAddCommGroup E
inst✝⁴ : NormedSpace 𝕜 E
F : Type u_3
inst✝³ : NormedAddCommGroup F
inst✝² : NormedSpace 𝕜 F
f : E →L[𝕜] F
inst✝¹ : CompleteSpace F
inst✝ : CompleteSpace E
surj : Surjective ⇑f
C : ℝ
C0 : C ≥ 0
g : F → E
hg : ∀ (y : F), dist (f (g y)) y ≤ 1 / 2 * ‖y‖ ∧ ‖g y‖ ≤ C * ‖y‖
h : F → F := fun y => y - f (g y)
hle : ∀ (y : F), ‖h y‖ ≤ 1 / 2 * ‖y‖
y : F
hnle : ∀ (n : ℕ), ‖h^[n] y‖ ≤ (1 / 2) ^ n * ‖y‖
u : ℕ → E := fun n => g (h^[n] y)
ule : ∀ (n : ℕ), ‖u n‖ ≤ (1 / 2) ^ n * (C * ‖y‖)
sNu : Summable fun n => ‖u n‖
su : Summable u
x : E := tsum u
x_ineq : ‖x‖ ≤ (2 * C + 1) * ‖y‖
fsumeq : ∀ (n : ℕ), f (∑ i in Finset.range n, u i) = y - h^[n] y
this : Tendsto (fun n => ∑ i in Finset.range n, u i) atTop (𝓝 x)
L₁ : Tendsto (fun n => y - (fun y => y - f (g y))^[n] y) atTop (𝓝 (f (∑' (n : ℕ), g ((fun y => y - f (g y))^[n] y))))
⊢ 1 / 2 < 1

Next tactic:
norm_num